Fast fixed-point neural blind-deconvolution algorithm

Authors:
S. Fiori
Affiliations:
Fac. of Eng., Perugia Univ., Terni, Italy
Venue:
IEEE Transactions on Neural Networks
Year:
2004

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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.