Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/345816
Type: Artigo
Title: A fast algorithm for sparse multichannel blind deconvolution
Author: Nose-Filho, Kenji
Takahata, André K.
Lopes, Renato
Romano, João M. T.
Abstract: We have addressed blind deconvolution in a multichannel framework. Recently, a robust solution to this problem based on a Bayesian approach called sparse multichannel blind deconvolution (SMBD) was proposed in the literature with interesting results. However, its computational complexity can be high. We have proposed a fast algorithm based on the minimum entropy deconvolution, which is considerably less expensive. We designed the deconvolution filter to minimize a normalized version of the hybrid l(1)/l(2)-norm loss function. This is in contrast to the SMBD, in which the hybrid l(1)/l(2)-norm function is used as a regularization term to directly determine the deconvolved signal. Results with synthetic data determined that the performance of the obtained deconvolution filter was similar to the one obtained in a supervised framework. Similar results were also obtained in a real marine data set for both techniques
Subject: Deconvolução
Country: Estados Unidos
Editor: Society of Exploration Geophysicists
Rights: Fechado
Identifier DOI: 10.1190/GEO2015-0069.1
Address: https://library.seg.org/doi/full/10.1190/geo2015-0069.1
Date Issue: 2016
Appears in Collections:FEEC - Artigos e Outros Documentos

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