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Security

Security is protection from, or resilience against, potential harm (or other unwanted coercion). Beneficiaries (technically referents) of security may be persons and social groups, objects and institutions, ecosystems, or any other entity or phenomenon vulnerable to unwanted change. Security mostly refers to protection from hostile forces, but it has a wide range of other senses: for example, as the absence of harm (e.g., freedom from want); as the presence of an essential good (e.g., food security); as resilience against potential damage or harm (e.g. secure foundations); as secrecy (e.g., a secure telephone line); as containment (e.g., a secure room or cell); and as a state of mind (e.g., emotional security).

Security is both a feeling and a state of reality. One can feel secure, while they aren't, but also feel insecure while they are secure. This distinction is usually not very clear to express in the English language.

The term is also used to refer to acts and systems whose purpose may be to provide security (security company, security police, security forces, security service, security agency, security guard, cyber security systems, security cameras, remote guarding). Security can be physical and virtual.

Etymology
The word 'secure' entered the English language in the 16th century. It is derived from Latin securus, meaning freedom from anxiety: se (without) + cura (care, anxiety).

Referent
A security referent is the focus of a security policy or discourse; for example, a referent may be a potential beneficiary (or victim) of a security policy or system.

Security referents may be persons or social groups, objects, institutions, ecosystems, or any other phenomenon vulnerable to unwanted change by the forces of its environment. The referent in question may combine many referents in the same way that, for example, a nation-state is composed of many individual citizens.

Context
The security context is the relationships between a security referent and its environment. From this perspective, security and insecurity depend first on whether the environment is beneficial or hostile to the referent and also on how capable the referent is of responding to their environment in order to survive and thrive.

Capabilities
The means by which a referent provides for security (or is provided for) vary widely. They include, for example:
 * Coercive capabilities, including the capacity to project coercive power into the environment (e.g., aircraft carriers, handguns, firearms);
 * Protective systems (e.g., lock, fence, wall, antivirus software, air defence system, armour)
 * Warning systems (e.g., alarm, radar)
 * Diplomatic and social action intended to prevent insecurity from developing (e.g. conflict prevention and transformation strategies); and
 * Policy intended to develop the lasting economic, physical, ecological, and other conditions of security (e.g., economic reform, ecological protection, progressive demilitarization, militarization).

Effects
Any action intended to provide security may have multiple effects. For example, an action may have a wide benefit, enhancing security for several or all security referents in the context; alternatively, the action may be effective only temporarily, benefit one referent at the expense of another, or be entirely ineffective or counterproductive.

Contested approaches
Approaches to security are contested and the subject of debate. For example, in debate about national security strategies, some argue that security depends principally on developing protective and coercive capabilities in order to protect the security referent in a hostile environment (and potentially to project that power into its environment, and dominate it to the point of strategic supremacy). Others argue that security depends principally on building the conditions in which equitable relationships can develop, partly by reducing antagonism between actors, ensuring that fundamental needs can be met, and also ensuring that differences of interest can be negotiated effectively.

Security contexts (examples)
The table shows some of the main domains where security concerns are prominent.

Informational
 * Application security
 * Communications security
 * Computer security
 * Data security
 * Digital security
 * Endpoint security
 * Information security
 * Internet security
 * Network security
 * Usable security

Physical
 * Airport security
 * Corporate security
 * Food security
 * Environmental security
 * Home security
 * Infrastructure security
 * Physical security
 * Port security/Supply chain security
 * Security bag
 * Security print
 * Border security
 * Security seal

Political
 * National security
 * Public security
 * Homeland security
 * Internal security
 * International security
 * Human security

Monetary
 * Economic security
 * Social security

The range of security contexts is illustrated by the following examples (in alphabetical order):

Computer security
Computer security, also known as cybersecurity or IT security, refers to the security of computing devices such as computers and smartphones, as well as computer networks such as private and public networks, and the Internet. The field has growing importance due to the increasing reliance on computer systems in most societies. It concerns the protection of hardware, software, data, people, and also the procedures by which systems are accessed. The means of computer security include the physical security of systems and the security of information held on them.

Corporate security
Corporate security refers to the resilience of corporations against espionage, theft, damage, and other threats. The security of corporations has become more complex as reliance on IT systems has increased, and their physical presence has become more highly distributed across several countries, including environments that are, or may rapidly become, hostile to them.

Environmental security
Environmental security, also known as ecological security, refers to the integrity of ecosystems and the biosphere, particularly in relation to their capacity to sustain a diversity of life-forms (including human life). The security of ecosystems has attracted greater attention as the impact of ecological damage by humans has grown.

Food security
Food security refers to the ready supply of, and access to, safe and nutritious food. Food security is gaining in importance as the world's population has grown and productive land has diminished through overuse and climate change.

Home security
Home security normally refers to the security systems used on a property used as a dwelling (commonly including doors, locks, alarm systems, lighting, fencing); and personal security practices (such as ensuring doors are locked, alarms are activated, windows are closed etc.)

Human security
Human security is an emerging paradigm that, in response to traditional emphasis on the right of nation-states to protect themselves, has focused on the primacy of the security of people (individuals and communities). The concept is supported by the United Nations General Assembly, which has stressed "the right of people to live in freedom and dignity" and recognized "that all individuals, in particular vulnerable people, are entitled to freedom from fear and freedom from want".

Information security
Information security refers to the security of information in any form. Spoken, written, digital, networked, technological, and procedural forms of information are all examples that may be covered in an information security management scheme. Computer security, IT security, ICT security, and network security are thus all subdomains of information security.

National security
National security refers to the security of a nation-state, including its people, economy, and institutions. In practice, state governments rely on a wide range of means, including diplomacy, economic power, and military capabilities.

Security concepts (examples)
Certain concepts recur throughout different fields of security:
 * Access control – the selective restriction of access to a place or other resource.
 * Assurance – an expression of confidence that a security measure will perform as expected.
 * Authorization – the function of specifying access rights/privileges to resources related to information security and computer security in general and to access control in particular.
 * Cipher – an algorithm that defines a set of steps to encrypt or decrypt information so that it is incomprehensible.
 * Countermeasure – a means of preventing an act or system from having its intended effect.
 * Defense in depth – a school of thought holding that a wider range of security measures will enhance security.
 * Exploit (noun) – a means of capitalizing on a vulnerability in a security system (usually a cyber-security system).
 * Identity management – enables the right individuals to access the right resources at the right times and for the right reasons.
 * Password – secret data, typically a string of characters, usually used to confirm a user's identity.
 * Resilience – the degree to which a person, community, nation or system is able to resist adverse external forces.
 * Risk – a possible event which could lead to damage, harm, or loss.
 * Security management – identification of an organization's assets (including people, buildings, machines, systems and information assets), followed by the development, documentation, and implementation of policies and procedures for protecting these assets.
 * Security seal
 * Threat – a potential source of harm.
 * Vulnerability – the degree to which something may be changed (usually in an unwanted manner) by external forces.

Perceptions of security
Since it is not possible to know with precision the extent to which something is 'secure' (and a measure of vulnerability is unavoidable), perceptions of security vary, often greatly. For example, a fear of death by earthquake is common in the United States (US), but slipping on the bathroom floor kills more people; and in France, the United Kingdom, and the US, there are far fewer deaths caused by terrorism than there are women killed by their partners in the home.

Another problem of perception is the common assumption that the mere presence of a security system (such as armed forces or antivirus software) implies security. For example, two computer security programs installed on the same device can prevent each other from working properly, while the user assumes that he or she benefits from twice the protection that only one program would afford.

Security theater is a critical term for measures that change perceptions of security without necessarily affecting security itself. For example, visual signs of security protections, such as a home that advertises its alarm system, may deter an intruder, whether or not the system functions properly. Similarly, the increased presence of military personnel on the streets of a city after a terrorist attack may help to reassure the public, whether or not it diminishes the risk of further attacks.

title: Security


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Security kernel

In telecommunication, the term security kernel has the following meanings:

 * 1) In computer and communications security, the central part of a computer or communications system hardware, firmware, and software that implements the basic security procedures for controlling access to system resources.
 * 2) A self-contained usually small collection of key security-related statements that (a) works as a part of an operating system to prevent unauthorized access to, or use of, the system and (b) contains criteria that must be met before specified programs can be accessed.
 * 3) Hardware, firmware, and software elements of a trusted computing base that implement the reference monitor concept.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: Security kernel


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Security management

Security management is the identification of an organization's assets i.e. including people, buildings, machines, systems and information assets, followed by the development, documentation, and implementation of policies and procedures for protecting assets.

An organization uses such security management procedures for information classification, threat assessment, risk assessment, and risk analysis to identify threats, categorize assets, and rate system vulnerabilities.

Loss prevention
Loss prevention focuses on what one's critical assets are and how they are going to protect them. A key component to loss prevention is assessing the potential threats to the successful achievement of the goal. This must include the potential opportunities that further the object (why take the risk unless there's an upside?) Balance probability and impact determine and implement measures to minimize or eliminate those threats.

Security risk management
The management of security risks applies the principles of risk management to the management of security threats. It consists of identifying threats (or risk causes), assessing the effectiveness of existing controls to face those threats, determining the risks' consequence(s), prioritizing the risks by rating the likelihood and impact, classifying the type of risk, and selecting an appropriate risk option or risk response. In 2016, a universal standard for managing risks was developed in The Netherlands. In 2017, it was updated and named: Universal Security Management Systems Standard 2017.

External

 * Strategic: Competition and customer demand.
 * Operational: Regulations, suppliers, and contract.
 * Financial: FX and credit.
 * Hazard: Natural disasters, cyber, and external criminal acts.
 * Compliance: New regulatory or legal requirements are introduced, or existing ones are changed, exposing the organization to a non-compliance risk if measures are not taken to ensure compliance.

Internal

 * Strategic: R&D.
 * Operational: Systems and processes (H&R, Payroll).
 * Financial: Liquidity and cash flow.
 * Hazard: Safety and security; employees and equipment.
 * Compliance: Concrete or potential changes in an organization's systems, processes, suppliers, etc. may create exposure to a legal or regulatory non-compliance.

Risk avoidance
The first choice to be considered is the possibility of eliminating the existence of criminal opportunity or avoiding the creation of such an opportunity. When additional considerations or factors are not created as a result of this action that would create a greater risk. For example, removing all the cash flow from a retail outlet would eliminate the opportunity for stealing the money, but it would also eliminate the ability to conduct business.

Risk reduction
When avoiding or eliminating the criminal opportunity conflicts with the ability to conduct business, the next step is reducing the opportunity of potential loss to the lowest level consistent with the function of the business. In the example above, the application of risk reduction might result in the business keeping only enough cash on hand for one day's operation.

Risk spreading
Assets that remain exposed after the application of reduction and avoidance are the subjects of risk spreading. This is the concept that limits loss or potential losses by exposing the perpetrator to the probability of detection and apprehension prior to the consummation of the crime through the application of perimeter lighting, barred windows, and intrusion detection systems. The idea is to reduce the time available for thieves to steal assets and escape without apprehension.

Risk transfer
The two primary methods of accomplishing risk transfer is to insure the assets or raise prices to cover the loss in the event of a criminal act. Generally speaking, when the first three steps have been properly applied, the cost of transferring risks is much lower.

Risk acceptance
All of the remaining risks must simply be assumed by the business as a part of doing business. Included with these accepted losses are deductibles, which have been made as part of the insurance coverage.

Intrusion detection

 * Alarm device.

Access control

 * Locks, simple or sophisticated, such as biometric authentication and keycard locks.

Physical security

 * Environmental elements (ex. Mountains, Trees, etc.).
 * Barricade.
 * Security guards (armed or unarmed) with wireless communication devices (e.g., two-way radio).
 * Security lighting (spotlight, etc.).
 * Security Cameras.
 * Motion Detectors.
 * IBNS containers for cash in transit.

Procedures

 * Coordination with law enforcement agencies.
 * Fraud management.
 * Risk Management.
 * CPTED.
 * Risk Analysis.
 * Risk Mitigation.
 * Contingency Planning.

title: Security management


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Self-synchronizing code

In coding theory, especially in telecommunications, a self-synchronizing code is a uniquely decodable code in which the symbol stream formed by a portion of one code word, or by the overlapped portion of any two adjacent code words, is not a valid code word. Put another way, a set of strings (called "code words") over an alphabet is called a self-synchronizing code if for each string obtained by concatenating two code words, the substring starting at the second symbol and ending at the second-last symbol does not contain any code word as substring. Every self-synchronizing code is a prefix code, but not all prefix codes are self-synchronizing.

Other terms for self-synchronizing code are synchronized code or, ambiguously, comma-free code. A self-synchronizing code permits the proper framing of transmitted code words provided that no uncorrected errors occur in the symbol stream; external synchronization is not required. Self-synchronizing codes also allow recovery from uncorrected errors in the stream; with most prefix codes, an uncorrected error in a single bit may propagate errors further in the stream and make the subsequent data corrupted.

Importance of self-synchronizing codes is not limited to data transmission. Self-synchronization also facilitates some cases of data recovery, for example of a digitally encoded text.

Examples

 * UTF-8 is self-synchronizing because the leading byte and subsequent bytes  of a multi-byte code point have different bit patterns.
 * High Level Data Link Control (HDLC)
 * Advanced Data Communication Control Procedures (ADCCP)
 * Fibonacci coding

Counterexamples:
 * The prefix code {00, 11} is not self-synchronizing; while 0, 1, 01 and 10 are not codes, 00 and 11 are.
 * The prefix code {ab,ba} is not self-synchronizing because abab contains ba.
 * The prefix code b∗a (using the Kleene star) is not self-synchronizing (even though any new code word simply starts after a) because code word ba contains code word a.

title: Self-synchronizing code


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Semiautomatic switching system

In telecommunication, the term semiautomatic switching system has the following meanings:

 * 1) In telephone systems, a switching system in which telephone operators receive call instructions orally from users and complete them by automatic equipment.
 * 2) At tape relay intermediate stations, the manual routing or rerouting of taped messages without rekeying them.

title: Semiautomatic switching system


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Sensitivity

Sensitivity may refer to:

Natural sciences

 * Sensitivity (physiology), the ability of an organism or organ to respond to external stimuli
 * Sensory processing sensitivity in humans
 * Sensitivity and specificity, statistical measures of the performance of binary classification tests
 * Allergic sensitivity, the strength of a reaction to an allergen
 * The inverse of resistance (ecology), the ability of populations to remain stable when subject to disturbance

Electronics

 * Sensitivity (electronics), the minimum magnitude of input signal required to produce a specified output signal
 * Sensitivity of a transducer, the relationship between input and output power
 * Sensitivity (electroacoustics)

Mathematics

 * Sensitivity (control systems), variations in process dynamics and control systems
 * Sensitivity analysis, apportionment of the uncertainty in the output of a mathematical model among its inputs
 * Sensitivity and specificity, statistical measures of the performance of binary classification tests

Other uses in science and technology

 * Sensitivity (explosives), the degree to which an explosive can be initiated by impact, heat or friction
 * Film speed, photographic film's sensitivity to light

Music

 * "Sensitivity" (Shapeshifters song), the fourth single from music group Shapeshifters
 * "Sensitivity" (song), a song by rhythm and blues singer Ralph Tresvant

Other uses

 * Information sensitivity, a property of information that may result in damage if disclosed
 * Price sensitivity, in economics

title: Sensitivity


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Separate-channel signaling

Separate-channel signaling is a form of signaling in which the whole or a part of one or more channels in a multichannel system is used to provide for supervisory and control signals for the message traffic channels.

The same channels, such as frequency bands or time slots, that are used for signaling are not used for message traffic. This is used for E-carrier telecommunications.

title: Separate-channel signaling


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Service termination point

In telecommunication, the service termination point is the last point of service rendered by a commercial carrier under applicable tariffs.

Usually, the service termination point is on the customer premises and corresponds to the demarcation point. The customer is responsible for equipment and operation from the service termination point to user end instruments.

title: Service termination point


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Shadow loss

In telecommunication, the term shadow loss has the following meanings:

 * 1) The attenuation caused to a radio signal by obstructions in the propagation path.
 * 2) In a reflector antenna, the relative reduction in the effective aperture of the antenna caused by the masking effect of other antenna parts, such as a feed horn or a secondary reflector, which parts obstruct the radiation path.

title: Shadow loss


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Shannon's law

Shannon's law may refer to:
 * Shannon's source coding theorem, which establishes the theoretical limits to lossless data compression
 * Shannon–Hartley theorem, which establishes the theoretical maximum rate at which data can be reliably transmitted over a noisy channel
 * Shannon's law (Arizona), a law against the firing of gunshots into the air, established after 14-year-old Shannon Smith was killed by a stray bullet in 1999

title: Shannon's law


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Sheath

Sheath, pronounced, may refer to:

 * Scabbard, a sheath for holding a sword, dagger, knife, or similar edged weapons, as well as long guns, such as rifles and shotguns.
 * The outer covering of an electrical cable
 * Debye sheath, a layer of a plasma in physics
 * Heliosheath, the region of the heliosphere beyond the termination shock
 * Kosha, an element in human being makeup according to Hinduist philosophy
 * Koteka, a penis sheath worn by some natives of New Guinea
 * Sheath (album), a 2003 album by LFO
 * Sheath dress, a type of dress

Biology

 * Carotid sheath, connective tissue around the neck's vascular compartment
 * Leaf sheath, the leaf base when it forms a vertical coating surrounding the stem
 * Myelin sheath, an insulating layer over the axon of a neuron
 * Preputial sheath, protective skin around the penis or clitoris
 * Clitoral sheath
 * Penile sheath, the foreskin into which a penis retracts
 * Rectus sheath, the laminas around abdominal muscles
 * Root sheath, the inner or epidermic coat around the root of a hair follicle
 * Tendon sheath, a synovial membrane surrounding a tendon in, for example, the fingers

title: Sheath


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Shield

A shield is a piece of personal armour held in the hand, which may or may not be strapped to the wrist or forearm. Shields are used to intercept specific attacks, whether from close-ranged weaponry or projectiles such as arrows, by means of active blocks, as well as to provide passive protection by closing one or more lines of engagement during combat.

Shields vary greatly in size and shape, ranging from large panels that protect the user's whole body to small models (such as the buckler) that were intended for hand-to-hand-combat use. Shields also vary a great deal in thickness; whereas some shields were made of relatively deep, absorbent, wooden planking to protect soldiers from the impact of spears and crossbow bolts, others were thinner and lighter and designed mainly for deflecting blade strikes (like the roromaraugi or qauata). Finally, shields vary greatly in shape, ranging in roundness to angularity, proportional length and width, symmetry and edge pattern; different shapes provide more optimal protection for infantry or cavalry, enhance portability, provide secondary uses such as ship protection or as a weapon and so on.

In prehistory and during the era of the earliest civilisations, shields were made of wood, animal hide, woven reeds or wicker. In classical antiquity, the Barbarian Invasions and the Middle Ages, they were normally constructed of poplar tree, lime or another split-resistant timber, covered in some instances with a material such as leather or rawhide and often reinforced with a metal boss, rim or banding. They were carried by foot soldiers, knights and cavalry.

Depending on time and place, shields could be round, oval, square, rectangular, triangular, bilabial or scalloped. Sometimes they took on the form of kites or flatirons, or had rounded tops on a rectangular base with perhaps an eye-hole, to look through when used with combat. The shield was held by a central grip or by straps with some going over or around the user's arm and one or more being held by the hand.

Often shields were decorated with a painted pattern or an animal representation to show their army or clan. These designs developed into systematized heraldic devices during the High Middle Ages for purposes of battlefield identification. Even after the introduction of gunpowder and firearms to the battlefield, shields continued to be used by certain groups. In the 18th century, for example, Scottish Highland fighters liked to wield small shields known as targes, and as late as the 19th century, some non-industrialized peoples (such as Zulu warriors) employed them when waging wars.

In the 20th and 21st century, shields have been used by military and police units that specialize in anti-terrorist actions, hostage rescue, riot control and siege-breaking.

Prehistory
The oldest form of shield was a protection device designed to block attacks by hand weapons, such as swords, axes and maces, or ranged weapons like sling-stones and arrows. Shields have varied greatly in construction over time and place. Sometimes shields were made of metal, but wood or animal hide construction was much more common; wicker and even turtle shells have been used. Many surviving examples of metal shields are generally felt to be ceremonial rather than practical, for example the Yetholm-type shields of the Bronze Age, or the Iron Age Battersea shield.

Ancient
Size and weight varied greatly. Lightly armored warriors relying on speed and surprise would generally carry light shields (pelte) that were either small or thin. Heavy troops might be equipped with robust shields that could cover most of the body. Many had a strap called a guige that allowed them to be slung over the user's back when not in use or on horseback. During the 14th–13th century BC, the Sards or Shardana, working as mercenaries for the Egyptian pharaoh Ramses II, utilized either large or small round shields against the Hittites. The Mycenaean Greeks used two types of shields: the "figure-of-eight" shield and a rectangular "tower" shield. These shields were made primarily from a wicker frame and then reinforced with leather. Covering the body from head to foot, the figure-of-eight and tower shield offered most of the warrior's body a good deal of protection in hand-to-hand combat. The Ancient Greek hoplites used a round, bowl-shaped wooden shield that was reinforced with bronze and called an aspis. The aspis was also the longest-lasting and most famous and influential of all of the ancient Greek shields. The Spartans used the aspis to create the Greek phalanx formation. Their shields offered protection not only for themselves but for their comrades to their left. Examples of Germanic wooden shields circa 350 BC – 500 AD survive from weapons sacrifices in Danish bogs.

The heavily armored Roman legionaries carried large shields (scuta) that could provide far more protection, but made swift movement a little more difficult. The scutum originally had an oval shape, but gradually the curved tops and sides were cut to produce the familiar rectangular shape most commonly seen in the early Imperial legions. Famously, the Romans used their shields to create a tortoise-like formation called a testudo in which entire groups of soldiers would be enclosed in an armoured box to provide protection against missiles. Many ancient shield designs featured incuts of one sort or another. This was done to accommodate the shaft of a spear, thus facilitating tactics requiring the soldiers to stand close together forming a wall of shields.

Post-classical
Typical in the early European Middle Ages were round shields with light, non-splitting wood like linden, fir, alder, or poplar, usually reinforced with leather cover on one or both sides and occasionally metal rims, encircling a metal shield boss. These light shields suited a fighting style where each incoming blow is intercepted with the boss in order to deflect it. The Normans introduced the kite shield around the 10th century, which was rounded at the top and tapered at the bottom. This gave some protection to the user's legs, without adding too much to the total weight of the shield. The kite shield predominantly features enarmes, leather straps used to grip the shield tight to the arm. Used by foot and mounted troops alike, it gradually came to replace the round shield as the common choice until the end of the 12th century, when more efficient limb armour allowed the shields to grow shorter, and be entirely replaced by the 14th century.

As body armour improved, knight's shields became smaller, leading to the familiar heater shield style. Both kite and heater style shields were made of several layers of laminated wood, with a gentle curve in cross section. The heater style inspired the shape of the symbolic heraldic shield that is still used today. Eventually, specialised shapes were developed such as the bouche, which had a lance rest cut into the upper corner of the lance side, to help guide it in combat or tournament. Free standing shields called pavises, which were propped up on stands, were used by medieval crossbowmen who needed protection while reloading.

In time, some armoured foot knights gave up shields entirely in favour of mobility and two-handed weapons. Other knights and common soldiers adopted the buckler, giving rise to the term "swashbuckler". The buckler is a small round shield, typically between 8 and 16 inches (20–40 cm) in diameter. The buckler was one of very few types of shield that were usually made of metal. Small and light, the buckler was easily carried by being hung from a belt; it gave little protection from missiles and was reserved for hand-to-hand combat where it served both for protection and offence. The buckler's use began in the Middle Ages and continued well into the 16th century.

In Italy, the targa, parma, and rotella were used by common people, fencers and even knights. The development of plate armour made shields less and less common as it eliminated the need for a shield. Lightly armoured troops continued to use shields after men-at-arms and knights ceased to use them. Shields continued in use even after gunpowder powered weapons made them essentially obsolete on the battlefield. In the 18th century, the Scottish clans used a small, round targe that was partially effective against the firearms of the time, although it was arguably more often used against British infantry bayonets and cavalry swords in close-in fighting.

During the 19th century, non-industrial cultures with little access to guns were still using war shields. Zulu warriors carried large lightweight shields called Ishlangu made from a single ox hide supported by a wooden spine. This was used in combination with a short spear (iklwa) and/or club. Other African shields include Glagwa from Cameroon or Nguba from Congo.

Law enforcement shields

Shields for protection from armed attack are still used by many police forces around the world. These modern shields are usually intended for two broadly distinct purposes. The first type, riot shields, are used for riot control and can be made from metal or polymers such as polycarbonate Lexan or Makrolon or boPET Mylar. These typically offer protection from relatively large and low velocity projectiles, such as rocks and bottles, as well as blows from fists or clubs. Synthetic riot shields are normally transparent, allowing full use of the shield without obstructing vision. Similarly, metal riot shields often have a small window at eye level for this purpose. These riot shields are most commonly used to block and push back crowds when the users stand in a "wall" to block protesters, and to protect against shrapnel, projectiles like stones and bricks, molotov cocktails, and during hand-to-hand combat.

The second type of modern police shield is the bullet-resistant ballistic shield, also called tactical shield. These shields are typically manufactured from advanced synthetics such as Kevlar and are designed to be bulletproof, or at least bullet resistant. Two types of shields are available:

 * 1) Light level IIIA shields are designed to stop pistol cartridges.
 * 2) Heavy level III and IV shields are designed to stop rifle cartridges.

Tactical shields often have a firing port so that the officer holding the shield can fire a weapon while being protected by the shield, and they often have a bulletproof glass viewing port. They are typically employed by specialist police, such as SWAT teams in high risk entry and siege scenarios, such as hostage rescue and breaching gang compounds, as well as in antiterrorism operations.

Law enforcement shields often have a large signs stating "POLICE" (or the name of a force, such as "US MARSHALS") to indicate that the user is a law enforcement officer.

title: Shield


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Shift register

A shift register is a type of digital circuit using a cascade of flip-flops where the output of one flip-flop is connected to the input of the next. They share a single clock signal, which causes the data stored in the system to shift from one location to the next. By connecting the last flip-flop back to the first, the data can cycle within the shifters for extended periods, and in this configuration they were used as computer memory, displacing delay-line memory systems in the late 1960s and early 1970s.

In most cases, several parallel shift registers would be used to build a larger memory pool known as a "bit array". Data was stored into the array and read back out in parallel, often as a computer word, while each bit was stored serially in the shift registers. There is an inherent trade-off in the design of bit arrays; putting more flip-flops in a row allows a single shifter to store more bits, but requires more clock cycles to push the data through all of the shifters before the data can be read back out again.

Shift registers can have both parallel and serial inputs and outputs. These are often configured as "serial-in, parallel-out" (SIPO) or as "parallel-in, serial-out" (PISO). There are also types that have both serial and parallel input and types with serial and parallel output. There are also "bidirectional" shift registers, which allow shifting in both directions: L → R or R → L. The serial input and last output of a shift register can also be connected to create a "circular shift register". A PIPO register (parallel in, parallel out) is simply a D-type register and is not a shift register, but is very fast – an output is given within a single clock pulse. A "universal" shift register provides bidirectional serial-in and serial-out, as well as parallel-in and parallel-out.

Destructive readout
These are the simplest kind of shift registers. The data string is presented at "data in" and is shifted right one stage each time "data advance" is brought high. At each advance, the bit on the far left (i.e. "data in") is shifted into the first flip-flop's output. The bit on the far right (i.e. "data out") is shifted out and lost.

The data is stored after each flip-flop on the "Q" output, so there are four storage "slots" available in this arrangement, hence it is a 4-bit register. To give an idea of the shifting pattern, imagine that the register holds 0000 (so all storage slots are empty). As "data in" presents 1,0,1,1,0,0,0,0 (in that order, with a pulse at "data advance" each time—this is called clocking or strobing) to the register, this is the result. The right hand column corresponds to the right-most flip-flop's output pin, and so on.

So the serial output of the entire register is 00010110. It can be seen that if data were to be continued to input, it would get exactly what was put in (10110000), but offset by four "data advance" cycles. This arrangement is the hardware equivalent of a queue. Also, at any time, the whole register can be set to zero by bringing the reset (R) pins high.

This arrangement performs destructive readout – each datum is lost once it has been shifted out of the right-most bit.

Serial-in parallel-out (SIPO)

This configuration allows conversion from serial to parallel format. Data input is serial, as described in the SISO section above. Once the data has been clocked in, it may be either read off at each output simultaneously, or it can be shifted out.

In this configuration, each flip-flop is edge triggered. All flip-flops operate at the given clock frequency. Each input bit makes its way down to the Nth output after N clock cycles, leading to parallel output.

In cases where the parallel outputs should not change during the serial loading process, it's desirable to use a latched or buffered output. In a latched shift register (such as the 74595) the serial data is first loaded into an internal buffer register, then upon receipt of a load signal the state of the buffer register is copied into a set of output registers. In general, the practical application of the serial-in/parallel-out shift register is to convert data from serial format on a single wire to parallel format on multiple wires.

Parallel-in serial-out (PISO)
This configuration has the data input on lines D1 through D4 in parallel format, D1 being the most significant bit. To write the data to the register, the Write/Shift control line must be held LOW. To shift the data, the W/S control line is brought HIGH and the registers are clocked. The arrangement now acts as a PISO shift register, with D1 as the Data Input. However, as long as the number of clock cycles is not more than the length of the data-string, the Data Output, Q, will be the parallel data read off in order. The animation below shows the write/shift sequence, including the internal state of the shift register.

Serial and parallel conversion
One of the most common uses of a shift register is to convert between serial and parallel interfaces.

Delay
Serial-in serial-out shift registers can be used as simple delay circuits.

Stack
Several bidirectional shift registers can also be connected in parallel for a hardware implementation of a stack.

More I/O pins
Shift registers are commonly attached to microcontrollers when more general-purpose input/output pins are required than are available, sometimes over a Serial Peripheral Interface in daisy chain configuration, which allows any number of binary devices to be accessed using only two to four pins, though more slowly than parallel I/O.

For more outputs, SIPO shift registers are used. The parallel outputs of the shift register and the desired state for all those devices can be sent out of the microcontroller using a single serial connection.

For more inputs, PISO shift registers are used. Each binary input (such as a button or more complicated circuitry) is attached to a parallel input of the shift register, then the data is sent back serially to the microcontroller.

Pulse extenders
Shift registers can also be used as pulse extenders. Compared to monostable multivibrators, the timing does not depend on component values, but it requires an external clock, and the timing accuracy is limited by the granularity of this clock. An example of such a pulse extender is the Ronja Twister, wherein five 74164 shift registers create the core of the timing logic this way (schematic).

Data processing
In early computers, shift registers were used to handle data processing: two numbers to be added were stored in two shift registers and clocked out into an arithmetic and logic unit (ALU) with the result being fed back to the input of one of the shift registers (the accumulator), which was one bit longer, since binary addition can only result in an answer that has the same size or is one bit longer.

Bitshift operations
Many computer languages include bitwise operations to "shift right" and "shift left" the data in a register, effectively dividing by two or multiplying by two for each place shifted.

Shift register memory
Very large serial-in serial-out shift registers (thousands of bits in size) were used in a similar manner to the earlier delay-line memory in some devices built in the early 1970s. Shift registers don't need many pins or address decoding logic, so was much cheaper than random-access memory back then. Such shift register memory was sometimes called circulating memory.

Datapoint 3300, for example, stored its terminal display of 25 rows of 72 columns of 6-bit upper-case characters using 54 200-bit shift registers (arranged in 6 tracks of 9 packs), providing storage for 1800 characters. The shift register design meant that scrolling the terminal display could be accomplished by simply pausing the display output to skip one line of characters. A similar design was used for the Apple I's terminal.

History
One of the first known examples of a shift register was in the Mark 2 Colossus, a code-breaking machine built in 1944. It was a six-stage device built of vacuum tubes and thyratrons. A shift register was also used in the IAS machine, built by John von Neumann and others at the Institute for Advanced Study in the late 1940s. Shift registers made their way into integrated circuits in the 1960s as evidenced by early patents from Frank Wanlass and Kent Smith working at General Instrument.

title: Shift register


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Shot noise

Shot noise or Poisson noise is a type of noise which can be modeled by a Poisson process.

In electronics shot noise originates from the discrete nature of electric charge. Shot noise also occurs in photon counting in optical devices, where shot noise is associated with the particle nature of light.

Origin
In a statistical experiment such as tossing a fair coin and counting the occurrences of heads and tails, the numbers of heads and tails after many throws will differ by only a tiny percentage, while after only a few throws outcomes with a significant excess of heads over tails or vice versa are common; if an experiment with a few throws is repeated over and over, the outcomes will fluctuate a lot. From the law of large numbers, one can show that the relative fluctuations reduce as the reciprocal square root of the number of throws, a result valid for all statistical fluctuations, including shot noise.

Shot noise exists because phenomena such as light and electric current consist of the movement of discrete (also called "quantized") 'packets'. Consider light—a stream of discrete photons—coming out of a laser pointer and hitting a wall to create a visible spot. The fundamental physical processes that govern light emission are such that these photons are emitted from the laser at random times; but the many billions of photons needed to create a spot are so many that the brightness, the number of photons per unit of time, varies only infinitesimally with time. However, if the laser brightness is reduced until only a handful of photons hit the wall every second, the relative fluctuations in number of photons, i.e., brightness, will be significant, just as when tossing a coin a few times. These fluctuations are shot noise.

The concept of shot noise was first introduced in 1918 by Walter Schottky who studied fluctuations of current in vacuum tubes.

Shot noise may be dominant when the finite number of particles that carry energy (such as electrons in an electronic circuit or photons in an optical device) is sufficiently small so that uncertainties due to the Poisson distribution, which describes the occurrence of independent random events, are significant. It is important in electronics, telecommunications, optical detection, and fundamental physics.

The term can also be used to describe any noise source, even if solely mathematical, of similar origin. For instance, particle simulations may produce a certain amount of "noise", where because of the small number of particles simulated, the simulation exhibits undue statistical fluctuations which don't reflect the real-world system. The magnitude of shot noise increases according to the square root of the expected number of events, such as the electric current or intensity of light. But since the strength of the signal itself increases more rapidly, the relative proportion of shot noise decreases and the signal-to-noise ratio (considering only shot noise) increases anyway. Thus shot noise is most frequently observed with small currents or low light intensities that have been amplified.

Signal-to-Noise
For large numbers, the Poisson distribution approaches a normal distribution about its mean, and the elementary events (photons, electrons, etc.) are no longer individually observed, typically making shot noise in actual observations indistinguishable from true Gaussian noise. Since the standard deviation of shot noise is equal to the square root of the average number of events N, the signal-to-noise ratio (SNR) is given by:

 * $$\mathrm{SNR} = \frac{N}{\sqrt{N}} = {\sqrt {N}}. \, $$

Thus when N is very large, the signal-to-noise ratio is very large as well, and any relative fluctuations in N due to other sources are more likely to dominate over shot noise. However, when the other noise source is at a fixed level, such as thermal noise, or grows slower than $$\sqrt{N}$$, increasing N (the DC current or light level, etc.) can lead to dominance of shot noise.

Electronic devices
Shot noise in electronic circuits consists of random fluctuations of DC current, which is due to electric current being the flow of discrete charges (electrons). Because the electron has such a tiny charge, however, shot noise is of relative insignificance in many (but not all) cases of electrical conduction. For instance 1 ampere of current consists of about $6.24$ electrons per second; even though this number will randomly vary by several billion in any given second, such a fluctuation is minuscule compared to the current itself. In addition, shot noise is often less significant as compared with two other noise sources in electronic circuits, flicker noise and Johnson–Nyquist noise. However, shot noise is temperature and frequency independent, in contrast to Johnson–Nyquist noise, which is proportional to temperature, and flicker noise, with the spectral density decreasing with increasing frequency. Therefore, at high frequencies and low temperatures shot noise may become the dominant source of noise.

With very small currents and considering shorter time scales (thus wider bandwidths) shot noise can be significant. For instance, a microwave circuit operates on time scales of less than a nanosecond and if we were to have a current of 16 nanoamperes that would amount to only 100 electrons passing every nanosecond. According to Poisson statistics the actual number of electrons in any nanosecond would vary by 10 electrons rms, so that one sixth of the time less than 90 electrons would pass a point and one sixth of the time more than 110 electrons would be counted in a nanosecond. Now with this small current viewed on this time scale, the shot noise amounts to 1/10 of the DC current itself.

The result by Schottky, based on the assumption that the statistics of electrons passage is Poissonian, reads for the spectral noise density at the frequency $$f$$,

S (f) = 2e\vert I \vert \ , $$ where $$e$$ is the electron charge, and $$I$$ is the average current of the electron stream. The noise spectral power is frequency independent, which means the noise is white. This can be combined with the Landauer formula, which relates the average current with the transmission eigenvalues $$T_n$$ of the contact through which the current is measured ($$n$$ labels transport channels). In the simplest case, these transmission eigenvalues can be taken to be energy independent and so the Landauer formula is

I = \frac{e^2}{\pi\hbar} V \sum_n T_n \ , $$ where $$V$$ is the applied voltage. This provides for

S = \frac{2e^3}{\pi\hbar} \vert V \vert \sum_n T_n \ , $$ commonly referred to as the Poisson value of shot noise, $$S_P$$. This is a classical result in the sense that it does not take into account that electrons obey Fermi–Dirac statistics. The correct result takes into account the quantum statistics of electrons and reads (at zero temperature)

S = \frac{2e^3}{\pi\hbar} \vert V \vert \sum_n T_n (1 - T_n)\. $$ It was obtained in the 1990s by Viktor Khlus, Gordey Lesovik (independently the single-channel case), and Markus Büttiker (multi-channel case). This noise is white and is always suppressed with respect to the Poisson value. The degree of suppression, $$F = S/S_P$$, is known as the Fano factor. Noises produced by different transport channels are independent. Fully open ($$T_n=1$$) and fully closed ($$T_n=0$$) channels produce no noise, since there are no irregularities in the electron stream.

At finite temperature, a closed expression for noise can be written as well. It interpolates between shot noise (zero temperature) and Nyquist-Johnson noise (high temperature).

Examples

 * Tunnel junction is characterized by low transmission in all transport channels, therefore the electron flow is Poissonian, and the Fano factor equals one.
 * Quantum point contact is characterized by an ideal transmission in all open channels, therefore it does not produce any noise, and the Fano factor equals zero. The exception is the step between plateaus, when one of the channels is partially open and produces noise.
 * A metallic diffusive wire has a Fano factor of 1/3 regardless of the geometry and the details of the material.
 * In 2DEG exhibiting fractional quantum Hall effect electric current is carried by quasiparticles moving at the sample edge whose charge is a rational fraction of the electron charge. The first direct measurement of their charge was through the shot noise in the current.

Effects of interactions
While this is the result when the electrons contributing to the current occur completely randomly, unaffected by each other, there are important cases in which these natural fluctuations are largely suppressed due to a charge build up. Take the previous example in which an average of 100 electrons go from point A to point B every nanosecond. During the first half of a nanosecond we would expect 50 electrons to arrive at point B on the average, but in a particular half nanosecond there might well be 60 electrons which arrive there. This will create a more negative electric charge at point B than average, and that extra charge will tend to repel the further flow of electrons from leaving point A during the remaining half nanosecond. Thus the net current integrated over a nanosecond will tend more to stay near its average value of 100 electrons rather than exhibiting the expected fluctuations (10 electrons rms) we calculated. This is the case in ordinary metallic wires and in metal film resistors, where shot noise is almost completely cancelled due to this anti-correlation between the motion of individual electrons, acting on each other through the coulomb force.

However this reduction in shot noise does not apply when the current results from random events at a potential barrier which all the electrons must overcome due to a random excitation, such as by thermal activation. This is the situation in p-n junctions, for instance. A semiconductor diode is thus commonly used as a noise source by passing a particular DC current through it.

In other situations interactions can lead to an enhancement of shot noise, which is the result of a super-poissonian statistics. For example, in a resonant tunneling diode the interplay of electrostatic interaction and of the density of states in the quantum well leads to a strong enhancement of shot noise when the device is biased in the negative differential resistance region of the current-voltage characteristics.

Shot noise is distinct from voltage and current fluctuations expected in thermal equilibrium; this occurs without any applied DC voltage or current flowing. These fluctuations are known as Johnson–Nyquist noise or thermal noise and increase in proportion to the Kelvin temperature of any resistive component. However both are instances of white noise and thus cannot be distinguished simply by observing them even though their origins are quite dissimilar.

Since shot noise is a Poisson process due to the finite charge of an electron, one can compute the root mean square current fluctuations as being of a magnitude

\sigma_i=\sqrt{2qI\,\Delta f} $$

where q is the elementary charge of an electron, Δf is the single-sided bandwidth in hertz over which the noise is considered, and I is the DC current flowing.

For a current of 100 mA, measuring the current noise over a bandwidth of 1 Hz, we obtain

\sigma_i = 0.18\,\mathrm{nA} \;. $$

If this noise current is fed through a resistor a noise voltage of

\sigma_v = \sigma_i \, R $$ would be generated. Coupling this noise through a capacitor, one could supply a noise power of

P = {\frac 1 2}qI\,\Delta f R. $$ to a matched load.

Detectors
The flux signal that is incident on a detector is calculated as follows, in units of photons: $$P = \frac {\Phi \, \Delta t} {\frac {hc}{\lambda}} $$

where c is the speed of light, and h is the Planck constant. Following Poisson statistics, the photon noise is calculated as the square root of the signal: $$S = \sqrt {P} $$

The SNR for a CCD camera can be calculated from the following equation: $$\mathrm{SNR} = \frac {I\cdot QE\cdot t} {\sqrt {I\cdot QE\cdot t + N_d\cdot t + N_r^2}}, $$ where:
 * I = photon flux (photons/pixel/second),
 * QE = quantum efficiency,
 * t = integration time (seconds),
 * Nd = dark current (electrons/pixel/sec),
 * Nr = read noise (electrons).

Optics
In optics, shot noise describes the fluctuations of the number of photons detected (or simply counted in the abstract) because they occur independently of each other. This is therefore another consequence of discretization, in this case of the energy in the electromagnetic field in terms of photons. In the case of photon detection, the relevant process is the random conversion of photons into photo-electrons for instance, thus leading to a larger effective shot noise level when using a detector with a quantum efficiency below unity. Only in an exotic squeezed coherent state can the number of photons measured per unit time have fluctuations smaller than the square root of the expected number of photons counted in that period of time. Of course there are other mechanisms of noise in optical signals which often dwarf the contribution of shot noise. When these are absent, however, optical detection is said to be "photon noise limited" as only the shot noise (also known as "quantum noise" or "photon noise" in this context) remains.

Shot noise is easily observable in the case of photomultipliers and avalanche photodiodes used in the Geiger mode, where individual photon detections are observed. However the same noise source is present with higher light intensities measured by any photo detector, and is directly measurable when it dominates the noise of the subsequent electronic amplifier. Just as with other forms of shot noise, the fluctuations in a photo-current due to shot noise scale as the square-root of the average intensity:

 * $$(\Delta I)^2 \ \stackrel{\mathrm{def}}{=}\  \langle\left(I-\langle I\rangle

\right)^2\rangle \propto I. $$

The shot noise of a coherent optical beam (having no other noise sources) is a fundamental physical phenomenon, reflecting quantum fluctuations in the electromagnetic field. In optical homodyne detection, the shot noise in the photodetector can be attributed to either the zero point fluctuations of the quantised electromagnetic field, or to the discrete nature of the photon absorption process. However, shot noise itself is not a distinctive feature of quantised field and can also be explained through semiclassical theory. What the semiclassical theory does not predict, however, is the squeezing of shot noise. Shot noise also sets a lower bound on the noise introduced by quantum amplifiers which preserve the phase of an optical signal.

title: Shot noise


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Sideband

In radio communications, a sideband is a band of frequencies higher than or lower than the carrier frequency, that are the result of the modulation process. The sidebands carry the information transmitted by the radio signal. The sidebands comprise all the spectral components of the modulated signal except the carrier. The signal components above the carrier frequency constitute the upper sideband (USB), and those below the carrier frequency constitute the lower sideband (LSB). All forms of modulation produce sidebands.

Sideband creation
We can illustrate the creation of sidebands with one trigonometric identity:

 * $$\cos(A)\cdot \cos(B) \equiv \tfrac{1}{2}\cos(A+B) + \tfrac{1}{2}\cos(A-B)$$

Adding $$\cos(A)$$ to both sides:

 * $$\cos(A)\cdot [1+\cos(B)] = \tfrac{1}{2}\cos(A+B) + \cos(A) + \tfrac{1}{2}\cos(A-B)$$

Substituting (for instance) $$A \triangleq 1000\cdot t$$  and  $$B \triangleq 100\cdot t,$$  where $$t$$ represents time:

 * $$\underbrace{\cos(1000\ t)}_{\text{carrier wave}}\cdot \underbrace{[1+\cos(100\ t)]}_{\text{amplitude modulation}}

= \underbrace{\tfrac{1}{2}\cos(1100\ t)}_{\text{upper sideband}} + \underbrace{\cos(1000\ t)}_{\text{carrier wave}} + \underbrace{\tfrac{1}{2}\cos(900\ t)}_{\text{lower sideband}}.$$

Adding more complexity and time-variation to the amplitude modulation also adds it to the sidebands, causing them to widen in bandwidth and change with time. In effect, the sidebands "carry" the information content of the signal.

Sideband Characterization
In the example above, a cross-correlation of the modulated signal with a pure sinusoid, $$\cos(\omega t),$$ is zero at all values of $$\omega$$ except 1100, 1000, and 900. And the non-zero values reflect the relative strengths of the three components. A graph of that concept, called a Fourier transform (or spectrum), is the customary way of visualizing sidebands and defining their parameters.

Amplitude modulation
Amplitude modulation of a carrier signal normally results in two mirror-image sidebands. The signal components above the carrier frequency constitute the upper sideband (USB), and those below the carrier frequency constitute the lower sideband (LSB). For example, if a 900kHz carrier is amplitude modulated by a 1kHz audio signal, there will be components at 899kHz and 901kHz as well as 900kHz in the generated radio frequency spectrum; so an audio bandwidth of (say) 7kHz will require a radio spectrum bandwidth of 14kHz. In conventional AM transmission, as used by broadcast band AM stations, the original audio signal can be recovered ("detected") by either synchronous detector circuits or by simple envelope detectors because the carrier and both sidebands are present. This is sometimes called double sideband amplitude modulation (DSB-AM), but not all variants of DSB are compatible with envelope detectors.

In some forms of AM, the carrier may be reduced, to save power. The term DSB reduced-carrier normally implies enough carrier remains in the transmission to enable a receiver circuit to regenerate a strong carrier or at least synchronise a phase-locked loop but there are forms where the carrier is removed completely, producing double sideband with suppressed carrier (DSB-SC). Suppressed carrier systems require more sophisticated circuits in the receiver and some other method of deducing the original carrier frequency. An example is the stereophonic difference (L-R) information transmitted in stereo FM broadcasting on a 38 kHz subcarrier where a low-power signal at half the 38-kHz carrier frequency is inserted between the monaural signal frequencies (up to 15kHz) and the bottom of the stereo information sub-carrier (down to 38–15kHz, i.e. 23kHz). The receiver locally regenerates the subcarrier by doubling a special 19 kHz pilot tone. In another example, the quadrature modulation used historically for chroma information in PAL television broadcasts, the synchronising signal is a short burst of a few cycles of carrier during the "back porch" part of each scan line when no image is transmitted. But in other DSB-SC systems, the carrier may be regenerated directly from the sidebands by a Costas loop or squaring loop. This is common in digital transmission systems such as BPSK where the signal is continually present.

If part of one sideband and all of the other remain, it is called vestigial sideband, used mostly with television broadcasting, which would otherwise take up an unacceptable amount of bandwidth. Transmission in which only one sideband is transmitted is called single-sideband modulation or SSB. SSB is the predominant voice mode on shortwave radio other than shortwave broadcasting. Since the sidebands are mirror images, which sideband is used is a matter of convention.

In SSB, the carrier is suppressed, significantly reducing the electrical power (by up to 12dB) without affecting the information in the sideband. This makes for more efficient use of transmitter power and RF bandwidth, but a beat frequency oscillator must be used at the receiver to reconstitute the carrier. If the reconstituted carrier frequency is wrong then the output of the receiver will have the wrong frequencies, but for speech small frequency errors are no problem for intelligibility. Another way to look at an SSB receiver is as an RF-to-audio frequency transposer: in USB mode, the dial frequency is subtracted from each radio frequency component to produce a corresponding audio component, while in LSB mode each incoming radio frequency component is subtracted from the dial frequency.

Frequency modulation
Frequency modulation also generates sidebands, the bandwidth consumed depending on the modulation index - often requiring significantly more bandwidth than DSB. Bessel functions can be used to calculate the bandwidth requirements of FM transmissions. Carson's rule is a useful approximation of bandwidth in several applications.

Effects
Sidebands can interfere with adjacent channels. The part of the sideband that would overlap the neighboring channel must be suppressed by filters, before or after modulation (often both). In broadcast band frequency modulation (FM), subcarriers above 75kHz are limited to a small percentage of modulation and are prohibited above 99 kHz altogether to protect the ±75 kHz normal deviation and ±100 kHz channel boundaries. Amateur radio and public service FM transmitters generally utilize ±5 kHz deviation.

To accurately reproduce the modulating waveform, the entire signal processing path of the system of transmitter, propagation path, and receiver must have enough bandwidth so that enough of the sidebands can be used to recreate the modulated signal to the desired degree of accuracy.

In a non-linear system such as an amplifier, sidebands of the original signal frequency components may be generated due to distortion. This is generally minimized but may be intentionally done for the fuzzbox musical effect.

title: Sideband


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Signal compression

Signal compression is the use of various techniques to increase the quality or quantity of signal parameters transmitted through a given telecommunications channel.

Types of signal compression include:

 * Bandwidth compression
 * Data compression
 * Dynamic range compression
 * Gain compression
 * Image compression
 * Lossy compression
 * One-way compression function

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title: Signal compression


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Signaling (telecommunications)

In telecommunication, signaling is the use of signals for controlling communications. This may constitute an information exchange concerning the establishment and control of a telecommunication circuit and the management of the network.

Classification
Signaling systems may be classified based on several principal characteristics.

In-band and out-of-band signaling
In the public switched telephone network (PSTN), in-band signaling is the exchange of call control information within the same physical channel, or within the same frequency band, that the message (the callers' voice) is using. An example is dual-tone multi-frequency signaling (DTMF), which is used on most telephone lines to customer premises.

Out-of-band signaling is telecommunication signaling on a dedicated channel separate from that used for the message. Out-of-band signaling has been used since Signaling System No. 6 (SS6) was introduced in the 1970s, and also in Signalling System No. 7 (SS7) in 1980 which became the standard for signaling among exchanges internationally.

In the mid-20th century, supervision signals on long-distance trunks in North America were primarily in-band, for example at 2600 Hz, necessitating a notch filter to prevent interference. Late in the century, all supervisory signals had been moved out of band. With the advent of digital trunks, supervision signals are carried by robbed bits or other bits in the E1-carrier dedicated to signaling.

Line versus register signaling
Line signaling is concerned with conveying information on the state of the line or channel, such as on-hook, off-hook (answer supervision and disconnect supervision, together referred to as supervision), ringing, and hook flash. Register signaling is concerned with conveying addressing information, such as the calling and/or called telephone number. In the early days of telephony, with operator handling calls, the addressing formation is by voice as "Operator, connect me to Mr. Smith please". In the first half of the 20th century, addressing formation is done by using a rotary dial, which rapidly breaks the line current into pulses, with the number of pulses conveying the address. Finally, starting in the second half of the century, address signaling is by DTMF.

Channel-associated versus common-channel signaling
Channel-associated signaling (CAS) employs a signaling channel that is dedicated to a specific bearer channel.

Common-channel signaling (CCS) employs a signaling channel which conveys signaling information relating to multiple bearer channels. These bearer channels, therefore, have their signaling channel in common.

Compelled signaling
Compelled signaling refers to signaling where the receipt of each signal from an originating register needs to be explicitly acknowledged before the next signal can be sent.

Most forms of R2 register signaling are compelled, while R1 multi-frequency signaling is not.

The term is only relevant in the case of signaling systems that use discrete signals (e.g. a combination of tones to denote one digit), as opposed to signaling systems which are message-oriented (such as SS7 and ISDN Q.931) where each message is able to convey multiple items of formation (e.g. multiple digits of the called telephone number).

Subscriber versus trunk signaling
Subscriber signaling refers to the signaling between the telephone and the telephone exchange. Trunk signaling is the signaling between exchanges.

Examples
Every signaling system can be characterized along each of the above axes of classification. A few examples:
 * DTMF is an in-band, channel-associated register signaling system. It is not compelled.
 * SS7 (e.g., TUP or ISUP) is an out-of-band, common-channel signaling system that incorporates both line and register signaling.
 * Metering pulses (depending on the country, these are 50 Hz, 12 kHz or 16 kHz pulses sent by the exchange to payphones or metering boxes) are out-of-band (because they do not fall within the frequency range used by the telephony signal, which is 300 through 3400 Hz) and channel-associated. They are generally regarded as line signaling, although this is open to debate.
 * E and M signaling (E&M) is an out-of-band channel-associated signaling system. The base system is intended for line signaling, but if decadic pulses are used it can also convey register information. E&M line signaling is however usually paired with DTMF register signaling.
 * By contrast, the L1 signaling system (which typically employs a 2280 Hz tone of various durations) is an in-band channel-associated signaling system as was the SF 2600 hertz system formerly used in the Bell System.
 * Loop start, ground start, reverse battery and revertive pulse systems are all DC, thus out of band, and all are channel-associated since the DC currents are on the talking wires.

Whereas common-channel signaling systems are out-of-band by definition, and in-band signaling systems are also necessarily channel-associated, the above metering pulse example demonstrates that there exist channel-associated signaling systems which are out-of-band.

title: Signaling (telecommunications)


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Signal-to-crosstalk ratio

The signal-to-crosstalk ratio at a specified point in a circuit is the ratio of the power of the wanted signal to the power of the unwanted signal from another channel.

The signals are adjusted in each channel so that they are of equal power at the zero transmission level point in their respective channels.

The signal-to-crosstalk ratio is usually expressed in dB.

title: Signal-to-crosstalk ratio


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Signal-to-noise ratio

Signal-to-noise ratio (SNR or S/N) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. SNR is defined as the ratio of signal power to noise power, often expressed in decibels. A ratio higher than 1:1 (greater than 0 dB) indicates more signal than noise.

SNR is an important parameter that affects the performance and quality of systems that process or transmit signals, such as communication systems, audio systems, radar systems, imaging systems, and data acquisition systems. A high SNR means that the signal is clear and easy to detect or interpret, while a low SNR means that the signal is corrupted or obscured by noise and may be difficult to distinguish or recover. SNR can be improved by various methods, such as increasing the signal strength, reducing the noise level, filtering out unwanted noise, or using error correction techniques.

SNR also determines the maximum possible amount of data that can be transmitted reliably over a given channel, which depends on its bandwidth and SNR. This relationship is described by the Shannon–Hartley theorem, which is a fundamental law of information theory.

SNR can be calculated using different formulas depending on how the signal and noise are measured and defined. The most common way to express SNR is in decibels, which is a logarithmic scale that makes it easier to compare large or small values. Other definitions of SNR may use different factors or bases for the logarithm, depending on the context and application.

Definition
One definition of signal-to-noise ratio is the ratio of the power of a signal (meaningful input) to the power of background noise (meaningless or unwanted input):

\mathrm{SNR} = \frac{P_\mathrm{signal}}{P_\mathrm{noise}}, $$ where $P$ is average power. Both signal and noise power must be measured at the same or equivalent points in a system, and within the same system bandwidth.

The signal-to-noise ratio of a random variable ($S$) to random noise $N$ is:

$$ \mathrm{SNR} = \frac{\mathrm{E}[S^2]}{\mathrm{E}[N^2]} \, , $$

where E refers to the expected value, which in this case is the mean square of $N$.

If the signal is simply a constant value of $s$, this equation simplifies to:

$$ \mathrm{SNR} = \frac{s^2}{\mathrm{E}[N^2]} \,. $$

If the noise has expected value of zero, as is common, the denominator is its variance, the square of its standard deviation $σ_{N}$.

The signal and the noise must be measured the same way, for example as voltages across the same impedance. Their root mean squares can alternatively be used according to:

\mathrm{SNR} = \frac{P_\mathrm{signal}}{P_\mathrm{noise}} = \left ( \frac{A_\mathrm{signal}}{A_\mathrm{noise} } \right )^2, $$ where $A$ is root mean square (RMS) amplitude (for example, RMS voltage).

Decibels
Because many signals have a very wide dynamic range, signals are often expressed using the logarithmic decibel scale. Based upon the definition of decibel, signal and noise may be expressed in decibels (dB) as

 * $$P_\mathrm{signal,dB} = 10 \log_{10} \left ( P_\mathrm{signal} \right ) $$

and

 * $$P_\mathrm{noise,dB} = 10 \log_{10} \left ( P_\mathrm{noise} \right ). $$

In a similar manner, SNR may be expressed in decibels as

\mathrm{SNR_{dB}} = 10 \log_{10} \left ( \mathrm{SNR} \right ). $$

Using the definition of SNR

\mathrm{SNR_{dB}} = 10 \log_{10} \left ( \frac{P_\mathrm{signal}}{P_\mathrm{noise}} \right ). $$

Using the quotient rule for logarithms

10 \log_{10} \left ( \frac{P_\mathrm{signal}}{P_\mathrm{noise}} \right ) = 10 \log_{10} \left ( P_\mathrm{signal} \right ) - 10 \log_{10} \left ( P_\mathrm{noise} \right ). $$

Substituting the definitions of SNR, signal, and noise in decibels into the above equation results in an important formula for calculating the signal to noise ratio in decibels, when the signal and noise are also in decibels:

\mathrm{SNR_{dB}} = {P_\mathrm{signal,dB} - P_\mathrm{noise,dB}}. $$

In the above formula, P is measured in units of power, such as watts (W) or milliwatts (mW), and the signal-to-noise ratio is a pure number.

However, when the signal and noise are measured in volts (V) or amperes (A), which are measures of amplitude, they must first be squared to obtain a quantity proportional to power, as shown below:

\mathrm{SNR_{dB}} = 10 \log_{10} \left [ \left ( \frac{A_\mathrm{signal}}{A_\mathrm{noise}} \right )^2 \right ] = 20 \log_{10} \left ( \frac{A_\mathrm{signal}}{A_\mathrm{noise}} \right ) = {A_\mathrm{signal,dB} - A_\mathrm{noise,dB}}. $$

Dynamic range
The concepts of signal-to-noise ratio and dynamic range are closely related. Dynamic range measures the ratio between the strongest un-distorted signal on a channel and the minimum discernible signal, which for most purposes is the noise level. SNR measures the ratio between an arbitrary signal level (not necessarily the most powerful signal possible) and noise. Measuring signal-to-noise ratios requires the selection of a representative or reference signal. In audio engineering, the reference signal is usually a sine wave at a standardized nominal or alignment level, such as 1 kHz at +4 dBu (1.228 VRMS).

SNR is usually taken to indicate an average signal-to-noise ratio, as it is possible that instantaneous signal-to-noise ratios will be considerably different. The concept can be understood as normalizing the noise level to 1 (0 dB) and measuring how far the signal 'stands out'.

Difference from conventional power
In physics, the average power of an AC signal is defined as the average value of voltage times current; for resistive (non-reactive) circuits, where voltage and current are in phase, this is equivalent to the product of the rms voltage and current:
 * $$ \mathrm{P} = V_\mathrm{rms}I_\mathrm{rms}

$$

\mathrm{P}= \frac{V_\mathrm{rms}^{2}}{R} = I_\mathrm{rms}^{2} R $$ But in signal processing and communication, one usually assumes that $$R=1 \Omega$$ so that factor is usually not included while measuring power or energy of a signal. This may cause some confusion among readers, but the resistance factor is not significant for typical operations performed in signal processing, or for computing power ratios. For most cases, the power of a signal would be considered to be simply

\mathrm{P}= V_\mathrm{rms}^{2} $$

Alternative definition
An alternative definition of SNR is as the reciprocal of the coefficient of variation, i.e., the ratio of mean to standard deviation of a signal or measurement:

\mathrm{SNR} = \frac{\mu}{\sigma} $$ where $$\mu$$ is the signal mean or expected value and $$\sigma$$ is the standard deviation of the noise, or an estimate thereof. Notice that such an alternative definition is only useful for variables that are always non-negative (such as photon counts and luminance), and it is only an approximation since $$\operatorname{E}\left[X^2 \right] = \sigma^2 + \mu^2 $$. It is commonly used in image processing,   where the SNR of an image is usually calculated as the ratio of the mean pixel value to the standard deviation of the pixel values over a given neighborhood.

Sometimes SNR is defined as the square of the alternative definition above, in which case it is equivalent to the more common definition:

\mathrm{SNR} = \frac{\mu^2}{\sigma^2} $$

This definition is closely related to the sensitivity index or d', when assuming that the signal has two states separated by signal amplitude $$\mu$$, and the noise standard deviation $$\sigma$$ does not change between the two states.

The Rose criterion (named after Albert Rose) states that an SNR of at least 5 is needed to be able to distinguish image features with certainty. An SNR less than 5 means less than 100% certainty in identifying image details.

Yet another alternative, very specific, and distinct definition of SNR is employed to characterize sensitivity of imaging systems; see Signal-to-noise ratio (imaging).

Related measures are the "contrast ratio" and the "contrast-to-noise ratio".

Amplitude modulation
Channel signal-to-noise ratio is given by
 * $$\mathrm{(SNR)_{C,AM}} = \frac{A_C^2 (1 + k_a^2 P)} {2 W N_0}

$$ where W is the bandwidth and $$k_a$$ is modulation index

Output signal-to-noise ratio (of AM receiver) is given by
 * $$\mathrm{(SNR)_{O,AM}} = \frac{A_c^2 k_a^2 P} {2 W N_0}

$$

Frequency modulation
Channel signal-to-noise ratio is given by
 * $$\mathrm{(SNR)_{C,FM}} = \frac{A_c^2} {2 W N_0}

$$

Output signal-to-noise ratio is given by
 * $$\mathrm{(SNR)_{O,FM}} = \frac{A_c^2 k_f^2 P} {2 N_0 W^3}

$$

Noise reduction

All real measurements are disturbed by noise. This includes electronic noise, but can also include external events that affect the measured phenomenon — wind, vibrations, the gravitational attraction of the moon, variations of temperature, variations of humidity, etc., depending on what is measured and of the sensitivity of the device. It is often possible to reduce the noise by controlling the environment.

Internal electronic noise of measurement systems can be reduced through the use of low-noise amplifiers.

When the characteristics of the noise are known and are different from the signal, it is possible to use a filter to reduce the noise. For example, a lock-in amplifier can extract a narrow bandwidth signal from broadband noise a million times stronger.

When the signal is constant or periodic and the noise is random, it is possible to enhance the SNR by averaging the measurements. In this case the noise goes down as the square root of the number of averaged samples.

Digital signals
When a measurement is digitized, the number of bits used to represent the measurement determines the maximum possible signal-to-noise ratio. This is because the minimum possible noise level is the error caused by the quantization of the signal, sometimes called quantization noise. This noise level is non-linear and signal-dependent; different calculations exist for different signal models. Quantization noise is modeled as an analog error signal summed with the signal before quantization ("additive noise").

This theoretical maximum SNR assumes a perfect input signal. If the input signal is already noisy (as is usually the case), the signal's noise may be larger than the quantization noise. Real analog-to-digital converters also have other sources of noise that further decrease the SNR compared to the theoretical maximum from the idealized quantization noise, including the intentional addition of dither.

Although noise levels in a digital system can be expressed using SNR, it is more common to use Eb/No, the energy per bit per noise power spectral density.

The modulation error ratio (MER) is a measure of the SNR in a digitally modulated signal.

Fixed point
For n-bit integers with equal distance between quantization levels (uniform quantization) the dynamic range (DR) is also determined.

Assuming a uniform distribution of input signal values, the quantization noise is a uniformly distributed random signal with a peak-to-peak amplitude of one quantization level, making the amplitude ratio 2n/1. The formula is then:

\mathrm{DR_{dB}} = \mathrm{SNR_{dB}} = 20 \log_{10}(2^n) \approx 6.02 \cdot n $$

This relationship is the origin of statements like "16-bit audio has a dynamic range of 96 dB". Each extra quantization bit increases the dynamic range by roughly 6 dB.

Assuming a full-scale sine wave signal (that is, the quantizer is designed such that it has the same minimum and maximum values as the input signal), the quantization noise approximates a sawtooth wave with peak-to-peak amplitude of one quantization level and uniform distribution. In this case, the SNR is approximately

\mathrm{SNR_{dB}} \approx 20 \log_{10} (2^n {\textstyle\sqrt {3/2}}) \approx 6.02 \cdot n + 1.761 $$

Floating point
Floating-point numbers provide a way to trade off signal-to-noise ratio for an increase in dynamic range. For n bit floating-point numbers, with n-m bits in the mantissa and m bits in the exponent:

\mathrm{DR_{dB}} = 6.02 \cdot 2^m $$

\mathrm{SNR_{dB}} = 6.02 \cdot (n-m) $$

The dynamic range is much larger than fixed-point, but at a cost of a worse signal-to-noise ratio. This makes floating-point preferable in situations where the dynamic range is large or unpredictable. Fixed-point's simpler implementations can be used with no signal quality disadvantage in systems where dynamic range is less than 6.02m. The very large dynamic range of floating-point can be a disadvantage, since it requires more forethought in designing algorithms.

Optical signals
Optical signals have a carrier frequency (about $200 THz$ and more) that is much higher than the modulation frequency. This way the noise covers a bandwidth that is much wider than the signal itself. The resulting signal influence relies mainly on the filtering of the noise. To describe the signal quality without taking the receiver into account, the optical SNR (OSNR) is used. The OSNR is the ratio between the signal power and the noise power in a given bandwidth. Most commonly a reference bandwidth of 0.1 nm is used. This bandwidth is independent of the modulation format, the frequency and the receiver. For instance an OSNR of 20 dB/0.1 nm could be given, even the signal of 40 GBit DPSK would not fit in this bandwidth. OSNR is measured with an optical spectrum analyzer.

Types and abbreviations
Signal to noise ratio may be abbreviated as SNR and less commonly as S/N. PSNR stands for peak signal-to-noise ratio. GSNR stands for geometric signal-to-noise ratio. SINR is the signal-to-interference-plus-noise ratio.

Other uses
While SNR is commonly quoted for electrical signals, it can be applied to any form of signal, for example isotope levels in an ice core, biochemical signaling between cells, or financial trading signals. The term is sometimes used metaphorically to refer to the ratio of useful information to false or irrelevant data in a conversation or exchange. For example, in online discussion forums and other online communities, off-topic posts and spam are regarded as that interferes with the  of appropriate discussion.

SNR can also be applied in marketing and how business professionals manage information overload. Managing a healthy signal to noise ratio can help business executives improve their KPIs (Key Performance Indicators).

Similar Concepts
The signal-to-noise ratio is similar to Cohen's d given by the difference of estimated means divided by the standard deviation of the data $$d=\frac{\bar{X}_1 - \bar{X}_2}{\text{SD}}=\frac{\bar{X}_1 - \bar{X}_2}{\sigma}=\frac {t} {\sqrt N}$$ and is related to the test statistic $$t$$ in the t-test.

title: Signal-to-noise ratio


text:
Signal transition

Signal transition, when referring to the modulation of a carrier signal, is a change from one significant condition to another.

Examples of signal transitions are a change from one electric current, voltage, or power level to another; a change from one optical power level to another; a phase shift; or a change from one frequency or wavelength to another.

Signal transitions are used to create signals that represent information, such as "0" and "1" or "mark" and "space".

title: Signal transition