Abstract

AbstractIn this chapter we will explain how adaptive filters are used in stochastic signal processing and estimation as well as detection. Real world signals are commonly random. The typical FIR or IIR filter cannot handle the random characteristics. Adaptive filters are better suited for stochastic and random signal processing. This type of signal processing is non-linear and is more complex than what is encountered with linear filters. One of the most common adaptive filtering approaches is the least square estimation. This approach minimizes an error computed as a difference between the predicted signal and measured signal. The applications of adaptive filters are very wide and the procedures of applying adaptive filters can be different from one area to another.

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