DocumentCode :
3393925
Title :
Formulation and algorithms for blind signal recovery
Author :
Salam, F.M. ; Gharbi, A.B. ; Erten, G.
Author_Institution :
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
Volume :
2
fYear :
1997
fDate :
3-6 Aug. 1997
Firstpage :
1233
Abstract :
We review some recent approximations of the averaged mutual information criterion and its use as a measure of signal independence. We describe an update law and its comparison with previous work in the literature. We also identify the link between the minimization of the mutual information and the information-maximization of the output entropy function of a (nonlinear) neural network. Example simulations demonstrate the performance of our recently developed algorithm in static and dynamic environments.
Keywords :
entropy; neural nets; signal reconstruction; state-space methods; averaged mutual information criterion; blind signal recovery; dynamic environment; mutual information; nonlinear neural network; output entropy function; signal independence; static environment; update law; Aging; Artificial neural networks; Circuits; Density measurement; Electric variables measurement; Finite impulse response filter; Laboratories; Minimization; Mutual information; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
Print_ISBN :
0-7803-3694-1
Type :
conf
DOI :
10.1109/MWSCAS.1997.662303
Filename :
662303
Link To Document :
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