On-line inference for hidden Markov models via particle filters
We consider the on-line Bayesian analysis of data by using a hidden Markov model, where inference is tractable conditional on the history of the state of the hidden component. A new particle filter algorithm is introduced and shown to produce promising results when analysing data of this type. The a...
Main Authors: | , |
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Format: | Journal article |
Language: | English |
Published: |
2003
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