Noise (signal processing)

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In signal processing, noise is a general term for unwanted (and, in general, unknown) modifications that a signal may suffer during capture, storage, transmission, processing, or conversion.[1]

Sometimes the word is also used to mean signals that are random (unpredictable) and carry no useful information; even if they are not interfering with other signals or may have been introduced intentionally, as in comfort noise.

Noise reduction, the recovery of the original signal from the noise-corrupted one, is a very common goal in the design of signal processing systems, especially filters. The mathematical limits for noise removal are set by information theory, namely the Shannon-Nyquist theorem.

Types of noise[edit]

Signal processing noise can be classified by its statistical properties (sometimes called the "color" of the noise) and by how it modifies the intended signal:

Noise in specific kinds of signals[edit]

Noise may arise in signals of interest to various scientific and technical fields, often with specific features:

Measures of noise in signals[edit]

A long list of noise measures have been defined to measure noise in signal processing: in absolute terms, relative to some standard noise level, or relative to the desired signal level. They include:

Technology for noise in signals[edit]

Almost every technique and device for signal processing has some connection to noise. Some random examples are:

See also[edit]

  • Signal-to-noise statistic, a mathematical formula to measure the difference of two values relative to their standard deviations

References[edit]

  1. ^ Vyacheslav Tuzlukov (2010), [ Signal Processing Noise], Electrical Engineering and Applied Signal Processing Series, CRC Press. 688 pages. ISBN 9781420041118