Understanding Several Adaptive Filter Algorithms Based on the Weight-update Strategy

This paper describes the comparison between adaptive filtering algorithms including least mean square (LMS), normalized least mean square (NLMS), recursive least square (RLS) and Kalman algorithm. We attempt to study their nonobvious nature which are often overlooked from the strategy how they adaptively update the weight. This joint perspective on adaptive filtering algorithms may help the intellectually curious reader expand thinking and deepen understanding.