Abstract:

In this paper,a novel LMS(Least Mean Square)algorithm with adaptive variable step size，namely,A NVSS,is proposed to solve the trade-of between the misadjustment and the convergence speed.In the proposed algorithm,the iteration step size is determined according to the present and past in error signals and by introducing a modification coefficient ρ and a forgetting factor λ(i).The algorithm is then analyzed and verified by simulation,with the resuhs indicating that the A NVSS algorithm constitutes a significant improvement in the convergence speed with very small misadjustment in stationary environments and is of better tracking capability,as compared with the traditional algorithms with variable step size.

Key words: least mean square algorithm, adaptive filtration, variable step size least mean square algorithm, forget-ting factor