Novel LMS algorithms based on status categorization

Abstract

Least Mean Square (LMS) is an effective adaptive filtering algorithm with advantages of robustness and simplicity. In this paper, we propose two new algorithms, Categorized Variable Step Size LMS (CVSSLMS) and Combined CVSSLMS (CCVSSLMS), based on the categorization of filter status. The step sizes of the proposed algorithms are dynamically updated by optimization for each state. Experiment results show that the proposed algorithms outperform conventional LMS algorithms in both simplicity and robustness.