Source separation as an exercise in logical induction

dc.creatorKnuth, Kevin H.
dc.date2002-04-25
dc.date.accessioned2026-07-07T05:47:30Z
dc.date.available2026-07-07T05:47:30Z
dc.descriptionWe examine the relationship between the Bayesian and information-theoretic formulations of source separation algorithms. This work makes use of the relationship between the work of Claude E. Shannon and the "Recent Contributions" by Warren Weaver (Shannon & Weaver 1949) as clarified by Richard T. Cox (1979) and expounded upon by Robert L. Fry (1996) as a duality between a logic of assertions and a logic of questions. Working with the logic of assertions requires the use of probability as a measure of degree of implication. This leads to a Bayesian formulation of the problem. Whereas, working with the logic of questions requires the use of entropy as a measure of the bearing of a question on an issue leading to an information-theoretic formulation of the problem.
dc.description10 pages. Presented at the MaxEnt 2000 conference in Gif-sur-Yvette Paris
dc.identifierhttps://arxiv.org/abs/physics/0204075
dc.identifierhttp://arxiv.org/abs/physics/0204075
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/84675
dc.subjectData Analysis, Statistics and Probability
dc.subjectInstrumentation and Detectors
dc.subjectMedical Physics
dc.titleSource separation as an exercise in logical induction
dc.typetext

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