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New algorithms for sparse multichannel blind deconvolution
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  • Kenji Nose Filho ,
  • Renato Lopes ,
  • Renan Brotto ,
  • Thonia Senna ,
  • João Romano
Kenji Nose Filho
Federal University of the ABC

Corresponding Author:[email protected]

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Renato Lopes
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Renan Brotto
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Thonia Senna
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João Romano
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In this paper we present three new algorithms for sparse multichannel blind deconvolution. The first algorithm is based on a cascade of a forward and a backward prediction error filter. The second consists in an alternating minimization algorithm for estimating both the reflectivity series and the seismic wavelet. The last one is a regularized version of the so called Euclid deconvolution, solved by the well known fast iterative shrinkage-thresholding algorithm (FISTA). Simulation results illustrate that the three algorithms presents some quite interesting results in both synthetic and real data.