A Class of Stochastic Adaptive Filters

In this chapter, we derive, study, and analyze a class of stochastic adaptive filters for SAEC with the WL model. All developed algorithms try to converge to the optimal Wiener filter. We start with the classical stochastic gradient algorithm, which is a good approximation of the deterministic algorithm studied in the previous chapter.

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