fast convergence alorithms for joint blind equalization....pdf (307.37 kB)
Fast convergence algorithms for joint blind equalization and source separation based upon the cross-correlation and constant modulus criterion
conference contributionposted on 2010-01-12, 16:23 authored by Yuhui Luo, Jonathon Chambers
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
- Mechanical, Electrical and Manufacturing Engineering
CitationLUO, 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
- VoR (Version of Record)
NotesThis 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.