Much of modern digital signal processing is concerned with the extraction of information from signals which are noisy, or which behave randomly while still revealing some attribute or parameter of a system or environment under observation. The term in popular use now for this kind of computation is ‘‘statistical signal processing,’’ and much of this handbook is devoted to this very subject. Statistical signal processing is classical statistical inference applied to problems of interest to electrical engineers, with the added twist that answers are often required in ‘‘real time,’’ perhaps seconds or less. Thus, computational algorithms are often studied hand-in-hand with statistics.