文章基本信息

标题：Performance Comparison of Different Variable Filters for Noise Cancellation in Real-Time Environment
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作者：B. Ananda Krishna ; G. V. P. Chandra Sekhar Yadav
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：2
页码：107-126
DOI：10.14257/ijsip.2016.9.2.10
出版社：SERSC
摘要：Elimination of noise from the signal is the major task in signal processing applications. Wiener filter removes noise efficiently but it requires large number of computations and it was updated with speed issue with adaptive filter. Adaptive filter has several algorithms to remove noise from the signal. This paper performs cancellation of noise from the signal using wiener filter and adaptive filter algorithms namely LMS, NLMS and RLS algorithms in real time environment. All these methods are compared using several parameters like step size, mean and variance of noise, mean square error, signal to noise ratio, speed, no. of. Iterations etc. In the existence work, the authors have compared the performance of the wiener filter & LMS algorithm in real time environment with sinusoidal input. This paper is extended by comparing different adaptive filter algorithms with the input taken in real time environment. It is observed that RLS algorithm performs noise cancellation better than all other algorithms. But it has high degree of complexity & cost while NLMS algorithm has moderate speed of performance and it is quietly chosen for several applications.
关键词：Adaptive Filter; Wiener Filter; LMS algorithms; NLMS algorithm; RLS algorithm; Performance Surface; Least Mean Square; Normalized Least Mean Square; Recursive Least Square; Variable Step Size; Performance Comparison; Mean Square Error; Minimum Mean Square Error; Signal to Noise Ratio; Variance; White Gaussian Noise; Sinusoidal Input; Real time Input