基于多尺度小波变换的变步长LMS滤波算法

对LMS自适应算法、基于抽样函数的变步长LMS算法和基于多尺度小波变换的自适应滤波算法进行了研究,在此基础上把变步长LMS算法与多尺度小波变换相结合,产生了新算法。该算法一方面可以克服固定步长LMS算法在收敛速度与收敛精度方面与步长因子的矛盾;另一方面,小波变换的引入减少了输入向量自相关矩阵的条件数,提高了收敛速度、跟踪性能和稳定性。最后对算法的性能进行了计算机仿真比较,仿真结果表明:基于多尺度小波变换的变步长LMS滤波算法具有较快的收敛速度和更强的抑噪能力。

An adaptive LMS algorithm with variable step based on multi-scale wavelet transform

The paper represents a new algorithm from the mergence of the variable step size LMS algorithm and the multi-scale wavelet transform on the basis of studies of LMS algorithm,variable step size LMS algorithm based on sample function,and LMS adaptive filtering algorithm based on multi-scale wavelet transform.On one hand,this new algorithm can overcome the contradiction between the fixed step size LMS algorithm＇s speed and accuracy of convergence and its step factors.On the other hand,the introduction of wavelet reduce the conditions of auto-correlation matrix of the input vector,and improve the speed,tracking performance and stability of contradication.Finally,the algorithm is compared by computer simulation,the simulation results show that a adaptive LMS algorithm with variable step based on multi-scale wavelet transform has faster convergence speed,better performance,and stronger robustness against noise and disturbance.