On adaptive HMM state estimation
Ford, Jason J. & Moore, John B. (1998) On adaptive HMM state estimation. IEEE Transactions on Signal Processing, 46(2), pp. 475-486.
In this paper new online adaptive hidden Markov model (HMM) state estimation schemes are developed, based on extended least squares (ELS) concepts and recursive prediction error (RPE) methods. The best of the new schemes exploit the idempotent nature of Markov chains and work with a least squares prediction error index, using a posterior estimates, more suited to Markov models then traditionally used in identification of linear systems.
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|Item Type:||Journal Article|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 1998 IEEE|
|Deposited On:||30 Oct 2014 23:48|
|Last Modified:||30 Oct 2014 23:48|
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