改进的WTLMS算法在主动噪声控制上应用

Improving WTLMS and Its Application on Active Noise Control

小波变换域LMS(WTLMS)算法比LMS算法收敛速度更快。主要把WTLMS算法应用到了主动噪声控制(ANC)系统中,改进了系统的自适应性能。仿真结果表明,WTLMS算法在IIR滤波器模型参数辨识上也是有效的,且输入的噪声信号频率成分越复杂,WTLMS算法比LMS算法收敛的速度越快。又分析了WTLMS算法结构上的冗余。提出了如何去除结构上冗余的方法,因此也提高了计算速度。此外,还研究了如何把整个系统从非因果系统变换成因果系统。

The wavelet transform domain least mean square （WTLMS） is known to have, in general, a faster convergence rate than the LMS algorithm. In this brief, the WTLMS algorithm was utilized to improve the adaptation of the active noise control （ANC） system. The simulation results show that the WTLMS algorithm also could be used to identify the parameters of the IIR filters, and it also shows that WTLMS have faster convergence rate than the LMS algorithm with the increasing of the frequency components of input noise signal. Through analyzing the redundancy existed in the WTLMS algorithm, how to remove structural redundancy was showed, which in turn reduced the computational load of the algorithm. The method of how to transform the non-causal system into causal system was given.