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 Nyquist–Shannon sampling 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