To test whether a set of samples can be well modeled as white
noise, we may compute its *sample autocorrelation* and verify
that it approaches an *impulse* in the limit as the number of
samples becomes large; this is another way of saying that successive
noise samples are *uncorrelated*. Equivalently, we may break the
set of samples into successive blocks across time, take an FFT of
each block, and average their squared magnitudes; if the resulting
average magnitude spectrum is *flat*, then the set of samples
looks like white noise. In the following sections, we will describe
these steps in further detail, culminating in *Welch's method*
for noise spectrum analysis, summarized in §6.9.

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