Performance Analysis of gradient decent adaptive filters for noise cancellation in Signal Processing

Abstract

Adaptive filtering is a very active area of research in the field of signal processing. Adaptive noise cancellation using adaptive filtering is an alternative technique of estimating signals corrupted by additive noise or interference. As received signal is corrupted by noise continuously where both received signal and noise are continuous signal, then a need of adaptive filter arises. This paper presents a comparative study of the various gradient decent based adaptive algorithms-recursive least square (RLS),least mean square (LMS) along with various categories of LMS such as normalized LMS(NLMS) Signum LMS(SLMS), fast block LMS(FBLMS) based noise canceller. The performance comparison of simulated model of noise canceller is presented in figures which shows the error signal, amplitudes of actualization coefficients and transmission characteristics.