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. - In: IEEE TRANSACTIONS ON NEURAL NETWORKS. - ISSN 1045-9227. - 15 (2):(2004), pp. 455-459.
Fast Fixed-Point Neural Blind Deconvolution Algorithm
FIORI, Simone
2004-01-01
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.File in questo prodotto:
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