Modelling the Probability Density of Markov Sources

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dc.creatorLuttrell, Stephen
dc.date2006-07-06
dc.date.accessioned2026-07-07T07:16:16Z
dc.date.available2026-07-07T07:16:16Z
dc.descriptionThis paper introduces an objective function that seeks to minimise the average total number of bits required to encode the joint state of all of the layers of a Markov source. This type of encoder may be applied to the problem of optimising the bottom-up (recognition model) and top-down (generative model) connections in a multilayer neural network, and it unifies several previous results on the optimisation of multilayer neural networks.
dc.description26 pages
dc.identifierhttps://arxiv.org/abs/cs/0607019
dc.identifierhttp://arxiv.org/abs/cs/0607019
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/113529
dc.subjectNeural and Evolutionary Computing
dc.subjectI.2.6; I.5.1
dc.titleModelling the Probability Density of Markov Sources
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