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The Hilbert Space Of Probability Mass Functions And Applications On Probabilistic Inference

The Hilbert space of probability mass functions (pmf) is introduced in this thesis. A factorization method for multivariate pmfs is proposed by using the tools provided by the Hilbert space of pmfs. The resulting factorization is special for two reasons. First, it reveals the algebraic relations between the involved random variables. Second, it determines the conditional independence relations between the random variables. Due to the first property of the resulting factorization, it can be shown that channel decoders can be employed in the solution of probabilistic inference problems other than decoding. This approach might lead to new probabilistic inference algorithms and new hardware options for the implementation of these algorithms. An example of new inference algorithms inspired by the idea of using channel decoder for other inference tasks is a multiple-input multiple-output (MIMO) detection algorithm which has a complexity of the square-root of the optimum MIMO detection algorithm.
Keywords: The Hilbert space of pmfs, factorization of pmfs, probabilistic inference, MIMO
detection, Markov random fields
iv

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613613/index.pdf
Date01 September 2011
CreatorsBayramoglu, Muhammet Fatih
ContributorsYilmaz, Ali Ozgur
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypePh.D. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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