Performance Analysis of an Improved Variable Step Size LMS Algorithm

By building a nonlinear function relationship between the step size μ(n) and the error signal e(n),this paper proposes an improved variable step size LMS(Least Mean Square) adaptive filtering algorithm.This variable step size algorithm avoids the shortcoming of changing step size of SVSLMS(variable step size LMS based on Sigmoid function).Also in the stage of adaptive steady state it has the virtue of e(n) slightly changing at point close to zero.Meanwhile the algorithm efficiently overcome the discrepancy between the convergence rate and the steady error.This algorithm constitutes a significant improvement in the identificated speed with very small steady error in stationary environment and is of better tracking capability,as compared with the traditional algorithms with step size.