The aim of the present 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 compared to algorithms of the same class.

Fast Fixed-Point Neural Blind Deconvolution Algorithm

FIORI, Simone
2004

Abstract

The aim of the present 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 compared to algorithms of the same class.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/33738
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