A fast algorithm for adaptive polynomial filtering

Abstract

This paper introduces a fast adaptive polynomial filtering algorithm, called LS-LMS algorithm, and analyzes its connections with RLS and with several QR decomposition based adaptive algorithms introduced in (Liu, 1995) and (Niemistö et al., 1996). Since the time-shift invariance property of the input data (Haykin, 1996, p. 763) is not required for the input vector, the algorithm is well suited for the identification of polynomial models. A noise cancelation application exemplifies the benefits of using the new algorithm.