Time-Domain Convolutive Blind Source Separation Employing Selective-Tap Adaptive Algorithms. (5th April 2007)

• Record Type: Journal Article
• Authors: Pan, Qiongfeng; Aboulnasr, Tyseer
• Other Names: Naylor Patrick A. Academic Editor.
• Is Part Of: EURASIP journal on audio, speech, and music processing. Volume 2007(2007)
• Publication Date: 2007-04-05
• Subjects: Sound -- Recording and reproducing -- Digital techniques -- Periodicals; Computer sound processing -- Periodicals; Computer sound processing; Sound -- Recording and reproducing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 620.2
• DOI: 10.1155/2007/92528
• Languages: English
• ISSNs: 1687-4714

Abstract

Abstract : 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.