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IJON
2002
98views more  IJON 2002»
13 years 4 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
NN
2000
Springer
167views Neural Networks» more  NN 2000»
13 years 4 months ago
Blind signal processing by the adaptive activation function neurons
The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to fo...
Simone Fiori
CVPR
2011
IEEE
12 years 12 months ago
Blind Deconvolution Using A Normalized Sparsity Measure
Blind image deconvolution is an ill-posed problem that requires regularization to solve. However, many common forms of image prior used in this setting have a major drawback in th...
Dilip Krishnan, Rob Fergus
DSP
2006
13 years 4 months ago
Blind image deconvolution via dispersion minimization
In linear image restoration, the point spread function of the degrading system is assumed known even though this information is usually not available in real applications. As a re...
C. Vural, William A. Sethares
ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
13 years 10 months ago
Blind separation of statistically independent signals with mixed sub-Gaussian and super-Gaussian probability distributions
— In the context of Independent Component Analysis (ICA), we propose a simple method for online estimation of activation functions in order to blindly separate instantaneous mixt...
Muhammad Tufail, Masahide Abe, Masayuki Kawamata