摘要
介绍一种将自适应噪声抵消算法应用于消除周期性工频脉冲干扰的方法。该方法利用周期sinc函数仿真工频脉冲干扰信号,与白噪声叠加作为参考输入,利用最小均方(Least Mean Square,LMS)算法与归一化最小均方(Normalized Least Mean Square,NLMS)算法进行自适应噪声抵消滤波仿真实验。MATLAB仿真处理结果显示,在无增益、增益饱和、增益过饱和这三种情况下,当信噪比为3 d B时,分别用LMS算法与NLMS算法滤波后可以清晰地分辨多次回波。
This paper describes a way of using adaptive noise cancellation to eliminate periodic power pulse interference and others. The method takes periodicsinc（x）=sin（πx）πx pulse signal, which simulates periodic power pulse inter-fering signal, with white noise as the reference input. The LMS algorithm and NLMS algorithm are used for the simu-lation of eliminating noise. In the three conditions of no gain, gain saturation and gain oversaturation, the outputs of MATLAB simulations for the input SNR of 3dB show that after using LMS algorithm and NLMS algorithm filtering, multiple echoes can be distinguished clearly.
出处
《声学技术》
CSCD
北大核心
2015年第4期342-346,共5页
Technical Acoustics
关键词
自适应噪声抵消
最小均方算法
归一化最小均方算法
工频脉冲干扰
adaptive noise cancellation
least mean square algorithm
normalized least mean square algorithm
power pulse interference
