Title :
Self-organizing blind MIMO deconvolution
Author :
Fijalkow, Inbar ; Gaussier, Philippe
Author_Institution :
ETIS/ENSEA, Cergy-Pontoise Univ., France
Abstract :
We address the dynamical architecture design of linear filters for the blind adaptive restoration of several sources from convolutive mixtures. We previously presented a self-organizing architecture based on the dynamical stability properties of neural network lateral inhibition rules. In this paper, we show the benefits of the proposed architecture in the case of more than two sources in terms of convergence rate and asymptotic properties
Keywords :
MIMO systems; adaptive signal processing; convergence; convolution; deconvolution; filtering theory; neural nets; self-adjusting systems; statistical analysis; asymptotic properties; blind MIMO deconvolution; blind adaptive restoration; convergence rate; convolutive source mixtures; dynamical architecture design; linear filters; neural network; self-organizing deconvolution; Deconvolution; Decorrelation; Delay; Finite impulse response filter; Gaussian processes; Image restoration; MIMO; Nonlinear filters; Signal restoration; Transfer functions;
Conference_Titel :
Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Caesarea
Print_ISBN :
0-7695-0140-0
DOI :
10.1109/HOST.1999.778747
