Variable step size LMS algorithm based on modified Sigmoid function

By studying the shortage of the traditional fixed step size least mean square (LMS) algorithm. This paper builds a nonlinear function relationship between μ and the error signal by reviewing the existing algorithm and presents a novel variable step size LMS adaptive filtering algorithm by improving Sigmoid function based on translation transformation. The selective of parameters and the performance of convergence are discussed. Theoretical analysis and simulation results show that the proposed variable step size LMS algorithm has better performance. Comparing with some existing algorithms, the algorithm improves their convergence performance.