DocumentCode :
2112886
Title :
A globally convergent approach for blind MIMO adaptive deconvolution
Author :
Touzni, A. ; Fijalkow, I. ; Larimore, M. ; Treichler, J.R.
Author_Institution :
CNRS, Cergy-Pontoise, France
Volume :
4
fYear :
1998
fDate :
12-15 May 1998
Firstpage :
2385
Abstract :
We address the deconvolution of MIMO linear mixtures. The approach is based on the construction of a hierarchical family of composite criteria involving CM criterion and second order statistics constraint. Although, the criteria are based on fourth order statistics, we give a complete proof of convergence of this structure. We show that each cost function leads to the restoration of one single source. Moreover the approach is naturally robust with respect to the channels order estimation. An adaptive algorithm is derived for the simultaneous estimation of all sources
Keywords :
MIMO systems; adaptive signal processing; convergence of numerical methods; deconvolution; higher order statistics; signal restoration; stochastic processes; MIMO linear mixtures; blind MIMO adaptive deconvolution; channel order estimation; constant modulus criterion; convergence; cost function; fourth order statistics; globally convergent approach; hierarchical composite criteria; second order statistics constraint; source estimation; source restoration; stochastic adaptive algorithm; Adaptive signal processing; Convergence; Costs; Deconvolution; MIMO; Robustness; Signal restoration; Source separation; Statistics; Wireless communication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
ISSN :
1520-6149
Print_ISBN :
0-7803-4428-6
Type :
conf
DOI :
10.1109/ICASSP.1998.681630
Filename :
681630
Link To Document :
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