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State Estimation Schemes for Independent Component Coupled Hidden Markov Models

Malcolm, William; Quadrianto, Novi; Aggoun, Lakhdar


Conventional Hidden Markov models generally consist of a Markov chain observed through a linear map corrupted by additive noise. This general class of model has enjoyed a huge and diverse range of applications, for example, speech processing, biomedical signal processing and more recently quantitative finance. However, a lesser known extension of this general class of model is the so-called Factorial Hidden Markov Model (FHMM). FHMMs also have diverse applications, notably in machine learning,...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Journal article
Source: Stochastic Analysis and Applications
DOI: 10.1080/07362991003708481


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