This project uses the least-mean-square algorithm for reducing the industrial-frequency noise of the transient electromagnetic signal that has been corrupted with noise. The problem is done for the TEM exploration method where the acquired signal is being corrupted by the noise of the industrial electricity, which is from either the electric wire in the air or the underground. In the following first a brief introduction of digital signal processing is given followed by a short summary of adaptive filters. Then we design an adaptive filter that is based on least-mean-square algorithm to reduce industrial-frequency interference. Both experiments of theoretical modeling and results of practical application show the designed algorithm of the adaptive filter is available and efficient. Finally I conclude by saying what I think about the work I have done.%在存在工频干扰的地区开展瞬变电磁法(TEM)工作时,工频干扰的强度通常很大,它的存在会使得反映地电异常的有用信号受到严重畸变,压制或去除工频干扰是数据预处理工作中的一项基础工作.针对这一问题,笔者设计了一种由可编程滤波器和自适应算法组成的具有自动调整滤波参数的滤波器.在进行滤波运算时,采用最小均方误差(LMS)算法不断地对滤波因子进行自动调节,使它们适应输入信号的相关特性,从而获得良好的滤波效果.理论数值模型和实际野外数据的验算表明,文中所设计的自适应滤波器具有很好的工频滤波效果.
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