Adaptive Filtering of Signals

Abstract

Traditional supervised adaptive filtering techniques use training sequences as a reference signal. In a communication scenery, this paradigm consists of periodically interrupting the transmission of information to send a training sequence. Adaptive filter coefficients are adjusted by comparing the filter’s output and the training sequence, in order to get the optimum filter coefficients. In this work, a bibliographic revision is presented, as well as simulation results that illustrate the method and demonstrate its viability.