White Noise
What is White Noise
Exactly?
White noise is a random signal (or process) with a flat power spectral
density. In other words, the signal's power spectral density has equal
power in any band, at any centre frequency, having a given bandwidth.
White noise is considered analogous to white light which contains all
frequencies.
An
infinite-bandwidth white noise signal is purely a theoretical construct.
By having power at all frequencies, the total power of such a signal is
infinite. In practice, a signal can be "white" with a flat spectrum over
a defined frequency band.
Statistical Properties:
The term white noise is also commonly applied to a noise signal in the
spatial domain which has zero autocorrelation over the relevant space
dimensions. The signal is then "white" in the spatial frequency domain
(this is equally true for signals in the angular frequency domain, e.g.
the distribution of a signal across all angles in the night sky). The
image below displays a finite length, discrete time realization of a
white noise process generated from a computer.
Being uncorrelated in time does not, however, restrict the values a
signal can take. Any distribution of values is possible (although it
must have zero DC component). For example, a binary signal which can
only take on the values 1 or 0 will be white if the sequence of zeros
and ones is statistically uncorrelated. Noise having a continuous
distribution, such as a
normal distribution,
can of course be white.
It is often
incorrectly assumed that Gaussian noise (i.e. noise with a Gaussian
amplitude distribution — see normal distribution) is necessarily white
noise. However, neither property implies the other. Gaussianity refers
to the way signal values are distributed, while the term 'white' refers
to correlations at two distinct times, which are independent of the
noise amplitude distribution.
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We can
therefore find Gaussian white noise, but also Poisson, Cauchy, etc.
white noises. Note that the distribution must have infinite variance.
Thus, the two words "Gaussian" and "white" are often both specified in
mathematical models of systems. Gaussian white noise is a good
approximation of many real-world situations and generates mathematically
tractable models. These models are used so frequently that the term
additive white Gaussian noise
has a standard abbreviation:
AWGN. Gaussian
white noise has the useful statistical property that its values are
independent.
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White Noise:
White noise
is a signal (or process) with a flat frequency spectrum in linear space.
In other words, the signal has equal power in any linear band, at any
center frequency, having a given bandwidth. For example, the 20 Hz
frequency range between 40 and 60 Hz contains the same amount of power
as the range between 4000 and 4020 Hz. An infinite-bandwidth white noise
signal is purely a theoretical construct. By having power at all
frequencies, the total power of such a signal would be infinite. In
practice, a signal is "white" if it has a flat spectrum over a defined
frequency band.
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Information is provided
by: www.wikipedia.com