## Sample Power Spectral Density

The Fourier transform of the sample autocorrelation function
(see (6.6)) is defined as the
*sample power spectral density* (PSD):

(7.11) |

This definition coincides with the classical

*periodogram*when is weighted differently (by a Bartlett window).

Similarly, the true power spectral density of a stationary stochastic
processes
is given by the Fourier transform of the true
autocorrelation function
, *i.e.*,

(7.12) |

For real signals, the autocorrelation function is always real and
even, and therefore the power spectral density is real and even for
all real signals.
An area under the PSD,
, comprises the contribution to the
*variance* of
from the frequency interval
. The total integral of the PSD gives
the total variance:

(7.13) |

again assuming is zero mean.

^{7.5}

Since the sample autocorrelation of white noise approaches an impulse, its PSD approaches a constant, as can be seen in Fig.6.1. This means that white noise contains all frequencies in equal amounts. Since white light is defined as light of all colors in equal amounts, the term ``white noise'' is seen to be analogous.

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Biased Sample Autocorrelation

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Sample Autocorrelation