General parameter-based adaptive extension to FIR filters

Abstract

A class of computationally efficient adaptive algorithms for transversal filters is discussed. The algorithms, which are based on the so-called general parameter method, use typically one or a few dynamically adjusted parameters, each to be added to a block of coefficients of a fixed basis FIR filter. Thus the overall filter is adapted so that the output error is minimized. The adaptive extension can be constructed as an 'add-on' element to be used in parallel with fixed-coefficient filters. An efficient implementation structure is proposed, and the stability and convergence properties of the multiple-parameter algorithm are analyzed.