Adaptive Estimation Techniques for Hidden Markov Models
• ML techniques for extracting Markov signals imbedded in a mixture of white Gaussian
noise and deterministic disturbances of known functional form with unknown
parameters. Two such disturbances are considered: periodic disturbances and polynomial
drift in the Markov states.
• Adaptive on-line schemes for estimating time-varying HMMs and Hidden semi Markov
models. We also propose on-line schemes for adaptively extracting Markov
signals with time varying statistics imbedded in a mixture of...[Show more]
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