A Variable Step-Size LMS Adaptive Filtering Algorithm

A variable step-size LMS algorithm which is based on the nonlinear functional relationship between the step-size and the error signal is presented. The new algorithm has better convergence properties at the beginning of adapting while ensuring small final misadjustment. Moreover the performance of the algorithm adapts to jump systems by using a hop-parameter alpha(n) to adjust the step-size and eliminates the disturbances of independent noise adjusting the step-size according to the square of the timed-averaged estimate of the autocorrelation of the current error signal e(n) and the previous error signal e(n-1). Computer simulation results confirm the algorithm is superior to the former algorithms in performance.