Entropy 2011, 13(9), 1730-1745; doi:10.3390/e13091730

Blind Deconvolution of Seismic Data Using f-Divergences

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Received: 15 August 2011; in revised form: 10 September 2011 / Accepted: 14 September 2011 / Published: 19 September 2011
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Abstract: This paper proposes a new approach to the seismic blind deconvolution problem in the case of band-limited seismic data characterized by low dominant frequency and short data records, based on Csiszár’s f-divergence. In order to model the probability density function of the deconvolved data, and obtain the closed form formula of Csiszár’s f-divergence, mixture Jones’ family of distributions (MJ) is introduced, by which a new criterion for blind deconvolution is constructed. By applying Neidell’s wavelet model to the inverse filter, we then make the optimization program for multivariate reduce to univariate case. Examples are provided showing the good performance of the method, even in low SNR situations.
Keywords: blind deconvolution; f-divergence; mixture Jones’ family of distributions
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MDPI and ACS Style

Zhang, B.; Gao, J.-H. Blind Deconvolution of Seismic Data Using f-Divergences. Entropy 2011, 13, 1730-1745.

AMA Style

Zhang B, Gao J-H. Blind Deconvolution of Seismic Data Using f-Divergences. Entropy. 2011; 13(9):1730-1745.

Chicago/Turabian Style

Zhang, Bing; Gao, Jing-Huai. 2011. "Blind Deconvolution of Seismic Data Using f-Divergences." Entropy 13, no. 9: 1730-1745.

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