A Comparison of Two Approaches: Maximum Entropy on the Mean (MEM) and Bayesian Estimation (BAYES) for Inverse Problems

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dc.creatorMohammad-Djafari, A.
dc.date2001-11-14
dc.date.accessioned2026-07-07T05:46:39Z
dc.date.available2026-07-07T05:46:39Z
dc.descriptionTo handle with inverse problems, two probabilistic approaches have been proposed: the maximum entropy on the mean (MEM) and the Bayesian estimation (BAYES). The main object of this presentation is to compare these two approaches which are in fact two different inference procedures to define the solution of an inverse problem as the optimizer of a compound criterion. Keywords: Inverse problems, Maximum Entropy on the Mean, Bayesian inference, Convex analysis.
dc.descriptionPresented at MaxEnt96. Appeared in Proceedings of the Maximum Entropy Conference, Berg-en-Dal, South Africa, M. Sears, V. Nedeljkovic, N.E. Pendock and S. Sibisi (Ed.), pp 77-91
dc.identifierhttps://arxiv.org/abs/physics/0111122
dc.identifierhttp://arxiv.org/abs/physics/0111122
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/84415
dc.subjectData Analysis, Statistics and Probability
dc.titleA Comparison of Two Approaches: Maximum Entropy on the Mean (MEM) and Bayesian Estimation (BAYES) for Inverse Problems
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