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- W2620719716 abstract "This paper presents a recursive prediction error algorithm which addresses the problem of computational complexity for on-line identification of hidden Markov models (HMMs). The particular class of HMMs considered has state-values which are clustered into groups. This allows a reformulation of the Markov model and results in a sub-optimal reduced order identification scheme. Actually, an exact definition of clustering is not discussed, rather, a general identification technique is presented for which the computational requirements are greatly reduced when the state-values are divided in some way into groups. The applicability to certain types of cluster patterns is tested via simulation studies." @default.
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- W2620719716 date "1995-08-01" @default.
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- W2620719716 title "Identification of Hidden Markov Models with Grouped State Values" @default.
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- W2620719716 doi "https://doi.org/10.1016/s1474-6670(17)45178-0" @default.
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