自适应变步长LMS滤波算法及分析

为了提高最小均方（LMS）自适应滤波算法的性能,通过建立步长因子与误差信号之间的非线性函数关系,提出一种自适应变步长LMS算法。该算法具有初始阶段和时变阶段步长自适应增大和稳态阶段步长很小的特点,消除了不相关噪声的影响,并且进一步克服了Sigmoid函数变步长LMS算法在自适应稳态阶段步长取值偏大的缺陷,计算机仿真结果与理论分析相一致,证实该算法优于传统算法。

Adaptive Variable-step Size LMS Filtering Algorithm and Its Analysis

In order to improve the performance of the variable step-size LMS(Least Mean Square)adaptive filtering algorithm,a novel algorithm based on the Sigmoid nonlinear functional relationship between the step-size and the error signal was proposed.The step-size of the algorithm increases adaptively at the beginning of the algorithm or when the channel is varying with time,and it would be smaller during the steady state.And the algorithm avoids the effects of the irrelevant noise.Furthermore,the proposed algorithm overcomes the deficiency of Sigmoid functional relationship in the process of step-size change of adaptive steady state.Computer simulation results verify the theoretical analysis and indicate that the algorithm outperforms the former algorithms.