Adaptive systems can be characterized by four items: the adaptive structure being modified, the configuration which contains the adaptive structure, the performance measure used to evaluate the current state of the adaptive structure, and the algorithm used to modify the structure to improve its performance. The adaptive FIR filter is the structure on which we focus in this introduction. We consider the adaptive filter's performance in configurations that include modeling, prediction, noise-cancelling and equalization. Using the mean-squared error as the performance measure, we consider a number of algorithms for adapting the weights of the FIR filter.
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