Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/51966
Título : Joint Bayesian separation and restoration of cosmic microwave background from convolutional mixtures
Autor : Kayabol, K, Sanz, J. L., Herranz, D., Kuruoglu, E. E., Salerno, E.
Fecha de publicación : 2011
Editor: Wiley-Blackwell
Resumen: 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
Identificadores: doi: 10.1111/j.1365-2966.2011.18783.x
issn: 0035-8711
e-issn: 1365-2966
Citación : Monthly Notices of the Royal Astronomical Society 415(2): 1334-1342 (2011)
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