Hidden Markov Models with Multiple Observers
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence（2007）
摘要
Hidden Markov models (HMMs) usually assume that the state transition matrices and the output models are time-invariant. Without this assumption, the parameters in a HMM may not be identifiable. In this paper, we propose a HMM with multiple observers such that its parameters are local identifiable without the time-invariant assumption. We show a sufficient condition for local identifiability of parameters in HMMS.
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关键词
identifiability.,multiple observers,hidden markov models,sufficient condition,time-invariant assumption,multiple observer,hidden markov model,state transition matrix,output model,local identifiability,state transition
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