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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|04Chapter5-8_Krishnamurthy.pdf||Chapters 5 to 8||6.5 MB||Adobe PDF|
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|Krishnamurthy Thesis 1991.pdf||12.95 MB||Adobe PDF|
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