Signal-to-noise ratio in the context of "Adaptive differential pulse-code modulation"

In digital audio using pulse-code modulation (PCM), bit depth is the number of bits of information in each sample, and it directly corresponds to the resolution of each sample. Examples of bit depth include Compact Disc Digital Audio, which uses 16 bits per sample, and DVD-Audio and Blu-ray Disc, which can support up to 24 bits per sample.

In basic implementations, variations in bit depth primarily affect the noise level from quantization error—thus the signal-to-noise ratio (SNR) and dynamic range. However, techniques such as dithering, noise shaping, and oversampling can mitigate these effects without changing the bit depth. Bit depth also affects bit rate and file size.

Stray light is light in an optical system which was not intended in the design. The light may be from the intended source, but follow paths other than intended, or it may be from a source other than that intended. This light will often set a working limit on the dynamic range of the system; it limits the signal-to-noise ratio or contrast ratio, by limiting how dark the system can be. Ocular straylight is stray light in the human eye.

A sensor array is a group of sensors, usually deployed in a certain geometry pattern, used for collecting and processing electromagnetic or acoustic signals. The advantage of using a sensor array over using a single sensor lies in the fact that an array adds new dimensions to the observation, helping to estimate more parameters and improve the estimation performance.For example an array of radio antenna elements used for beamforming can increase antenna gain in the direction of the signal while decreasing the gain in other directions, i.e., increasing signal-to-noise ratio (SNR) by amplifying the signal coherently. Another example of sensor array application is to estimate the direction of arrival of impinging electromagnetic waves. The related processing method is called array signal processing. A third examples includes chemical sensor arrays, which utilize multiple chemical sensors for fingerprint detection in complex mixtures or sensing environments. Application examples of array signal processing include radar/sonar, wireless communications, seismology, machine condition monitoring, astronomical observations fault diagnosis, etc.

Using array signal processing, the temporal and spatial properties (or parameters) of the impinging signals interfered by noise and hidden in the data collected by the sensor array can be estimated and revealed. This is known as parameter estimation.

Johnson–Nyquist noise (thermal noise, Johnson noise, or Nyquist noise) is the voltage or current noise generated by the thermal agitation of the charge carriers (usually the electrons) inside an electrical conductor at equilibrium, which happens regardless of any applied voltage. Thermal noise is present in all electrical circuits, and in sensitive electronic equipment (such as radio receivers) can drown out weak signals, and can be the limiting factor on sensitivity of electrical measuring instruments. Thermal noise is proportional to absolute temperature, so some sensitive electronic equipment such as radio telescope receivers are cooled to cryogenic temperatures to improve their signal-to-noise ratio. The generic, statistical physical derivation of this noise is called the fluctuation-dissipation theorem, where generalized impedance or generalized susceptibility is used to characterize the medium.

Thermal noise in an ideal resistor is approximately white, meaning that its power spectral density is nearly constant throughout the frequency spectrum (Figure 2). When limited to a finite bandwidth and viewed in the time domain (as sketched in Figure 1), thermal noise has a nearly Gaussian amplitude distribution.

Single-ended signaling is the simplest and most commonly used method of transmitting electrical signals over wires. One wire carries a varying voltage that represents the signal, while the other wire is connected to a reference voltage, usually ground. The main alternative to single-ended signaling is called differential signaling where the two conductors carry signals equal in magnitude but of opposite electric polarity.

Single-ended signaling is less expensive to implement than differential, but it has a distinct disadvantage: a single-ended system requires a power supply voltage equal to the maximum amplitude of the signal to be received whereas a differential system only requires a voltage half of the signal amplitude to be received. For a given power supply voltage then, a differential system produces signals of twice the amplitude and therefore has twice as good noise immunity (6 dB higher signal-to-noise ratio) as a single-ended system.

An astronomical filter is a telescope accessory consisting of an optical filter used by amateur astronomers to improve the details and contrast of celestial objects, either for viewing or for photography. Research astronomers, on the other hand, use various band-pass filters for photometry on telescopes, in order to obtain measurements which reveal objects' astrophysical properties, such as stellar classification and placement of a celestial body on its Wien curve.

Most astronomical filters work by blocking a specific part of the color spectrum above and below a bandpass, significantly increasing the signal-to-noise ratio of the interesting wavelengths, and so making the object gain detail and contrast. While the color filters transmit certain colors from the spectrum and are usually used for observation of the planets and the Moon, the polarizing filters work by adjusting the brightness, and are usually used for the Moon. The broad-band and narrow-band filters transmit the wavelengths that are emitted by the nebulae (by the hydrogen and oxygen atoms), and are frequently used for reducing the effects of light pollution.

Audio normalization is the application of a constant amount of gain to an audio recording to bring the amplitude to a target level (the norm). Because the same amount of gain is applied across the entire recording, the signal-to-noise ratio and relative dynamics are unchanged. Normalization is one of the functions commonly provided by a digital audio workstation.

Two principal types of audio normalization exist. Peak normalization adjusts the recording based on the highest signal level present in the recording. Loudness normalization adjusts the recording based on perceived loudness.

Sound can be recorded and stored and played using either digital or analog techniques. Both techniques introduce errors and distortions in the sound, and these methods can be systematically compared. Musicians and listeners have argued over the superiority of digital versus analog sound recordings. Arguments for analog systems include the absence of fundamental error mechanisms which are present in digital audio systems, including aliasing and associated anti-aliasing filter implementation, jitter and quantization noise. Advocates of digital point to the high levels of performance possible with digital audio, including excellent linearity in the audible band and low levels of noise and distortion.

Two prominent differences in performance between the two methods are the bandwidth and the signal-to-noise ratio (S/N ratio). The bandwidth of the digital system is determined, according to the Nyquist frequency, by the sample rate used. The bandwidth of an analog system is dependent on the physical and electronic capabilities of the analog circuits. The S/N ratio of a digital system may be limited by the bit depth of the digitization process, but the electronic implementation of conversion circuits introduces additional noise. In an analog system, other natural analog noise sources exist, such as flicker noise and imperfections in the recording medium. Other performance differences are specific to the systems under comparison, such as the ability for more transparent filtering algorithms in digital systems and the harmonic saturation and speed variations of analog systems.

Radio jamming is the deliberate blocking of or interference with wireless communications. In some cases, jammers work by the transmission of radio signals that disrupt telecommunications by decreasing the signal-to-noise ratio.

The concept can be used in wireless data networks to disrupt information flow. It is a common form of censorship in totalitarian countries, in order to prevent foreign radio stations in border areas from reaching the country.

Noise shaping is a technique typically used in digital audio, image, and video processing, usually in combination with dithering, as part of the process of quantization or bit-depth reduction of a signal. Its purpose is to increase the apparent signal-to-noise ratio of the resultant signal. It does this by altering the spectral shape of the error that is introduced by dithering and quantization, such that the noise power is at a lower level in frequency bands at which noise is considered to be less desirable and at a correspondingly higher level in bands where it is considered to be more desirable. A popular noise shaping algorithm used in image processing is known as ‘Floyd Steinberg dithering’; and many noise shaping algorithms used in audio processing are based on an ‘Absolute threshold of hearing’ model.

In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate. Theoretically, a bandwidth-limited signal can be perfectly reconstructed if sampled at the Nyquist rate or above it. The Nyquist rate is defined as twice the bandwidth of the signal. Oversampling is capable of improving resolution and signal-to-noise ratio, and can be helpful in avoiding aliasing and phase distortion by relaxing anti-aliasing filter performance requirements.

A signal is said to be oversampled by a factor of N if it is sampled at N times the Nyquist rate.

An information filtering system is a system that removes redundant or unwanted information from an information stream using (semi)automated or computerized methods prior to presentation to a human user. Its main goal is the management of the information overload and increment of the semantic signal-to-noise ratio. To do this the user's profile is compared to some reference characteristics. These characteristics may originate from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach).

Whereas in information transmission signal processing filters are used against syntax-disrupting noise on the bit-level, the methods employed in information filtering act on the semantic level.

A low-noise amplifier (LNA) is an electronic component that amplifies a very low-power signal without significantly degrading its signal-to-noise ratio (SNR). Any electronic amplifier will increase the power of both the signal and the noise present at its input, but the amplifier will also introduce some additional noise. LNAs are designed to minimize that additional noise, by choosing special components, operating points, and circuit topologies. Minimizing additional noise must balance with other design goals such as power gain and impedance matching.

LNAs are found in radio communications systems, amateur radio stations, medical instruments and electronic test equipment. A typical LNA may supply a power gain of 100 (20 decibels (dB)) while decreasing the SNR by less than a factor of two (a 3 dB noise figure (NF)). Although LNAs are primarily concerned with weak signals that are just above the noise floor, they must also consider the presence of larger signals that cause intermodulation distortion.