Paper Info
Title
Fast fixed-point neural blind-deconvolution algorithm
Abstract
The aim of this letter is to introduce a new blind-deconvolution algorithm based on fixed-point optimization of a "Bussgang"-type cost function. The cost function relies on approximate Bayesian estimation achieved by an adaptive neuron. The main feature of the presented algorithm is fast convergence that guarantees good deconvolution performances with limited computational demand as compared with algorithms of the same class.
Year
DOI
Venue
2004
10.1109/TNN.2004.824258
IEEE Transactions on Neural Networks
Keywords
DocType
Volume
belief networks,blind equalisers,convergence,deconvolution,neural nets,optimisation,Bussgang-type cost function,adaptive neuron,fast convergence,fixed-point optimization,neural Bayesian estimation,neural blind deconvolution algorithm
Journal
15
Issue
ISSN
Citations 
2
1045-9227
21
PageRank 
References 
Authors
1.45
9
1
Name
Order
Citations
PageRank
Simone Fiori149452.86