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Information-theoretic methods for estimating of complicated probability distributions

Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based meth...

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Detalles Bibliográficos
Autor principal: Zong, Zhi
Lenguaje:eng
Publicado: Elsevier Science 2006
Materias:
Acceso en línea:http://cds.cern.ch/record/2066186
Descripción
Sumario:Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neur