Application and Performance Analysis of LMS Algorithm with Variable Step Size in System Identification

An improved Least Mean Square(LMS) algorithm with adaptive step size is proposed.Utilizing the fourth power of instantaneous error and forgetting factor to adjust the step size,the improved algorithm increases adaptively at the beginning of the algorithm or unknown system changing with time,and it is smaller during the steady state.Meanwhile the algorithm efficiently overcome the discrepancy between the convergence rate and the steady error.When this algorithm is applied to system identification,a significant improvement can be achieved in the identifying speed,smaller steady error and better tracking capability,as compared with the traditional algorithms with adaptive step size.