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Additive white Gaussian noise (AWGN) is a basic noise model used in information theory to mimic the effect of many random processes that occur in nature. The modifiers denote specific characteristics: Additive because it is added to any noise that might be intrinsic to the information system.
White noise is commonly used in the production of electronic music, usually either directly or as an input for a filter to create other types of noise signal. It is used extensively in audio synthesis , typically to recreate percussive instruments such as cymbals or snare drums which have high noise content in their frequency domain. [ 8 ]
A special case is white Gaussian noise, in which the values at any pair of times are identically distributed and statistically independent (and hence uncorrelated). In communication channel testing and modelling, Gaussian noise is used as additive white noise to generate additive white Gaussian noise.
White noise. Additive white Gaussian noise; Black noise; Gaussian noise; Pink noise or flicker noise, with 1/f power spectrum; Brownian noise, with 1/f 2 power spectrum; Contaminated Gaussian noise, whose PDF is a linear mixture of Gaussian PDFs; Power-law noise; Cauchy noise; Multiplicative noise, multiplies or modulates the intended signal
The transformation is called "whitening" because it changes the input vector into a white noise vector. Several other transformations are closely related to whitening: the decorrelation transform removes only the correlations but leaves variances intact, the standardization transform sets variances to 1 but leaves correlations intact,
Colored noise can be computer-generated by first generating a white noise signal, Fourier-transforming it, then multiplying the amplitudes of the different frequency components with a frequency-dependent function. [26] Matlab programs are available to generate power-law colored noise in one or any number of dimensions.
Maximum-ratio combining is the optimum combiner for independent additive white Gaussian noise channels. MRC can restore a signal to its original shape. The technique was invented by American engineer Leonard R. Kahn [1] in 1954.
Another way to generate a signal with the required Doppler power spectrum is to pass a white Gaussian noise signal through a Gaussian filter with a frequency response equal to the square-root of the Doppler spectrum required. Although simpler than the models above, and non-deterministic, it presents some implementation questions related to ...