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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Modified Clipped LMS Algorithm Mojtaba Lotfizad | EURASIP Journal on Applied Signal Processing 2005 8 1229-1234 2005 Hindawi Publishing Corporation Modified Clipped LMS Algorithm Mojtaba Lotfizad Department of Electrical Engineering Tarbiat Modarres University P.O. Box 14115-143 Tehran Iran Email lotfizad@modares.ac.ir Hadi Sadoghi Yazdi Department of Electrical Engineering Tarbiat Modarres University P.O. Box 14115-143 Tehran Iran Email sadoghEy@yahoo.com Received 30 May 2004 Revised 22 January 2005 Recommended for Publication by Mark Kahrs A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method namely the clipped LMS and uses a three-level quantization 1 0 -1 scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also it can be proved that the proposed modified clipped LMS MCLMS algorithm has better tracking than the LMS algorithm. In addition this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm but this causes slower convergence. Computer simulations confirm the mathematical analysis presented. Keywords and phrases adaptive filter LMS algorithm clipped LMS algorithm modified clipped LMS algorithm. 1. INTRODUCTION Adaptive signal processing has been one of the fastest growing fields of research in recent years. It has attained its popularity due to a broad range of useful applications in such diverse areas as communications radar sonar seismology navigation and control systems and biomedical electronics. The LMS adaptive filter is very popular due to its simplicity but even simpler approaches are required for many realtime applications several different versions of the LMS algorithm have been proposed in the literature 1
