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Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/51966
Title: Joint Bayesian separation and restoration of cosmic microwave background from convolutional mixtures
Authors: Kayabol, K; Sanz, J. L.; Herranz, D.; Kuruoglu, E. E.; Salerno, E.
Issue Date: 2011
Publisher: Wiley-Blackwell
Citation: Monthly Notices of the Royal Astronomical Society 415(2): 1334-1342 (2011)
Abstract: We propose a Bayesian approach to joint source separation and restoration for astrophysical diffuse sources. We constitute a prior statistical model for the source images by using their gradient maps. We assume a t-distribution for the gradient maps in different directions, because it is able to fit both smooth and sparse data. A Monte Carlo technique, called Langevin sampler, is used to estimate the source images and all the model parameters are estimated by using deterministic techniques.
URI: http://hdl.handle.net/10261/51966
Identifiers: doi: 10.1111/j.1365-2966.2011.18783.x
issn: 0035-8711
e-issn: 1365-2966
DOI: 10.1111/j.1365-2966.2011.18783.x
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