7
Random Signals and Spectral Estimation
7.1 Introduction
Random signals are signals with elements that cannot be predicted or derived exactly from other elements. In our previous examples of discrete signals, we used finite data vectors or analytic signals that are either periodic or transient; that is, we used signals that can be described completely in simple terms.
When a signal has random components and cannot be described analytically, we may be able to describe it in terms of its statistical properties, which we discuss in this chapter. There are two basic sources of the most commonly used statistical properties: (1) the amplitude distribution of the random signal and (2) the autocorrelation function or, equivalently, the ...
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