The probabilistic multi-hypothesis tracking (PMHT) algorithm is extended for application to classification. The PMHT model is reformulated as a bank of continuous-state hidden Markov models, allowing for supervised learning of the class-conditional probability density models, and for likelihood evaluation of multicomponent signals.
Multicomponent signal classification using the PMHT algorithm
01.01.2002
523525 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Multicomponent Signal Classification using the PMHT Algorithm
British Library Conference Proceedings | 2002
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