A non stationary LMS algorithm for adaptive tracking of a Markov time-varying system

We propose in this paper a. new adaptive algorithm which is designed to track system represented by a filter which has a P order markovian timo evolution. The Non Stationary LMS (NSLMS) algorithm is aide to identify the unknown order and parameters of the markov model. Ananalysis of the performances of the adaptive filter when the input is i.i.d. shows that the NSLMS presents better performances than the classical LMS. In particular, this superiority occurs when the system time evolution is so fast that the tracking with LMS is harmful.