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» Nonlinear Processing in LGN Neurons
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IJON
2002
98views more  IJON 2002»
13 years 5 months ago
Blind deconvolution by simple adaptive activation function neuron
The `Bussgang' algorithm is one among the most known blind deconvolution techniques in the adaptive signal processing literature. It relies on a Bayesian estimator of the sou...
Simone Fiori
JCNS
2010
121views more  JCNS 2010»
13 years 8 days ago
Pattern orthogonalization via channel decorrelation by adaptive networks
The early processing of sensory information by neuronal circuits often includes a reshaping of activity patterns that may facilitate the further processing of stimulus representat...
Stuart D. Wick, Martin T. Wiechert, Rainer W. Frie...
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
13 years 11 months ago
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
Yung-Keun Kwon, Byung Ro Moon
ICONIP
2007
13 years 6 months ago
Making a Robot Dance to Music Using Chaotic Itinerancy in a Network of FitzHugh-Nagumo Neurons
We propose a technique to make a robot execute free and solitary dance movements on music, in a manner which simulates the dynamic alternations between synchronisation and autonomy...
Jean-Julien Aucouturier, Yuta Ogai, Takashi Ikegam...
NIPS
2003
13 years 6 months ago
Predicting Speech Intelligibility from a Population of Neurons
A major issue in evaluating speech enhancement and hearing compensation algorithms is to come up with a suitable metric that predicts intelligibility as judged by a human listener...
Jeff Bondy, Ian C. Bruce, Suzanna Becker, Simon Ha...