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- DescriptionAs more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors' general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.
- Author(s)John B. Moore,Lakhdar Aggoun,Robert J. Elliott
- PublisherSpringer-Verlag New York Inc.
- Date of Publication01/12/2010
- SubjectComputing: General
- Series TitleStochastic Modelling and Applied Probability
- Series Part/Volume Number29
- Place of PublicationNew York, NY
- Country of PublicationUnited States
- ImprintSpringer-Verlag New York Inc.
- Content Noteblack & white illustrations
- Weight605 g
- Width156 mm
- Height234 mm
- Spine20 mm
- Format DetailsTrade paperback (US)
- Edition Statement1st ed. Softcover of orig. ed. 1995
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