منابع مشابه
Learning Hierarchical Hidden Markov Models with General State Hierarchy
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The hierarchical hidden Markov model (HHMM) is an extension of the hidden Markov model to include a hierarchy of the hidden states. This form of hierarchical modeling has been found useful in applications such as handwritten character recognition, behavior recognition, video indexing, and text retrieval. Nevertheless, the state hierarchy in the original HHMM is restricted to a tree structure. T...
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ژورنال
عنوان ژورنال: ETS Research Report Series
سال: 2007
ISSN: 2330-8516
DOI: 10.1002/j.2333-8504.2007.tb02061.x