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Title: Fast convergence algorithms for joint blind equalization and source separation based upon the cross-correlation and constant modulus criterion
Authors: Luo, Yuhui
Chambers, Jonathon
Keywords: MIMO systems
Adaptive signal processing
Blind equalisers
Convergence of numerical methods
Correlation methods
Least mean squares methods
Issue Date: 2002
Publisher: © IEEE
Citation: LUO, Y. and CHAMBERS, J., 2002. Fast convergence algorithms for joint blind equalization and source separation based upon the cross-correlation and constant modulus criterion. IN: IEEE International Conference on Acoustics, Speech, and Signal Processing, 13-17 May, Volume 3, pp. III-3065 - III-3068
Abstract: To solve the problem of joint blind equalization and source separation, two new quasi-Newton adaptive algorithms with rapid convergence property are proposed, based on the cross-correlation and constant modulus (CC-CM) criterion, namely the block-Shanno cross-correlation and constant modulus algorithm (BS-CCCMA) and the fast quasi-Newton crosscorrelation and constant modulus algorithm (FQN-CCCMA). Simulations studies are used to show that the convergence properties of these algorithms are much improved upon those of the conventional LMS-CCCMA algorithm
Description: This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/servlet/opac?punumber=7874. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/ICASSP.2002.1005334
URI: https://dspace.lboro.ac.uk/2134/5780
ISBN: 0780374029
ISSN: 1520-6149
Appears in Collections:Conference Papers and Contributions (Mechanical, Electrical and Manufacturing Engineering)

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