Maximum mean square deviation adaptive filtering algorithm with the same step-size via convex combination - Guo-sheng RUI; Jun MIAO; Yang ZHANG; Lin WANG (Tongxin xuebao)
Aimed at poor tracking performance of NLMS filter and filter under time-varying channel,a same step-size convex combination of the maximum mean square deviation algorithm was presented.The algorithm convexly combined two different adaptive filters with the same step-size based on a criterion of maximum mean square deviation.So the proposed filter could keep good dynamic performance in the time-varying channel and stability of mean square characteristics in convergence stage.Theoretical analysis and simulation results show that in the sparse and non-sparse state the proposed algorithm indicates the fastest convergence rate compared with NLMS,PNLMS and IPNLMS algorithm.In the fuzzy state,the performance of proposed algorithm is superior to the above three.Additionally,the steady-state performance of mean square also keeps well.