tailieunhanh - Báo cáo hóa học: " Research Article Time-Domain Convolutive Blind Source Separation Employing Selective-Tap Adaptive Algorithms Qiongfeng Pan and Tyseer Aboulnasr"

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: Research Article Time-Domain Convolutive Blind Source Separation Employing Selective-Tap Adaptive Algorithms Qiongfeng Pan and Tyseer Aboulnasr | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2007 Article ID 92528 11 pages doi 2007 92528 Research Article Time-Domain Convolutive Blind Source Separation Employing Selective-Tap Adaptive Algorithms Qiongfeng Pan and Tyseer Aboulnasr School of Information Technology and Engineering University of Ottawa Ottawa ON Canada K1N 6N5 Received 30 June 2006 Accepted 24 January 2007 Recommended by Patrick A. Naylor We investigate novel algorithms to improve the convergence and reduce the complexity of time-domain convolutive blind source separation BSS algorithms. First we propose MMax partial update time-domain convolutive BSS MMax BSS algorithm. We demonstrate that the partial update scheme applied in the MMax LMS algorithm for single channel can be extended to multichannel time-domain convolutive BSS with little deterioration in performance and possible computational complexity saving. Next we propose an exclusive maximum selective-tap time-domain convolutive BSS algorithm XM BSS that reduces the interchannel coherence of the tap-input vectors and improves the conditioning of the autocorrelation matrix resulting in improved convergence rate and reduced misalignment. Moreover the computational complexity is reduced since only half of the tap inputs are selected for updating. Simulation results have shown a significant improvement in convergence rate compared to existing techniques. Copyright 2007 Q. Pan and T. Aboulnasr. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Blind source separation BSS 1 2 is an established area of work estimating source signals based on information about observed mixed signals at the sensors that is the estimation is performed without exploiting information about either the source signals or the mixing system. .

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