DocumentCode
960841
Title
Fast fixed-point neural blind-deconvolution algorithm
Author
Fiori, Simone
Author_Institution
Fac. of Eng., Perugia Univ., Terni, Italy
Volume
15
Issue
2
fYear
2004
fDate
3/1/2004 12:00:00 AM
Firstpage
455
Lastpage
459
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.
Keywords
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; Bayesian methods; Convergence; Cost function; Deconvolution; Distortion; Finite impulse response filter; Geophysical measurements; Image storage; Neurons; Signal processing; Algorithms; Neural Networks (Computer);
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2004.824258
Filename
1288248
Link To Document