一种新的LMS自适应滤波算法分析仿真研究

摘要

传统变步长最小均方(LMS)算法存在收敛速度慢、易受噪声干扰等缺点,为了提高算法的性能,通过对变步长LMS算法进行分析研究,在步长因子x(n)与误差信号e(n)的相关统计量之间建立一种新的非线性函数关系,提出了一种新的变步长LMS自适应滤波算法.该算法采用误差信号的自相关时间均值来调节步长,并用绝对估计误差的扰动量以加快自适应滤波器抽头权向量的收敛.理论分析与计算机仿真结果表明:与SVSLMS和G-SVSLMS算法比较,该算法具有较快的收敛速度、较小的稳态误差以及较强的抗干扰能力.%The common variable step size LMS algorithm has many weakness, such as poor convergence speed and sensitivity to noise. A new variable step size adaptive filter algorithm is presented. A new non-linear function between step factor and error signal is established. In this algorithm,the step size factor is adjusted by the absolute value of the product of the current and former errors. The algorithm also introduces the disturbance of the absolute estimation error to update the tapping vector of the self-adaptive filter. The theoretical analysis and simulation results shows that compared with SVSLMS and G-SVSLMS algorithm, the new algorithm has faster convergence speed,lower steady state error and better performance of noise suppression.