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Item Details
| Title:
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INFERENCE IN HIDDEN MARKOV MODELS
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| By: |
Olivier Cappe, Eric Moulines, Tobias Ryden |
| Format: |
Paperback |
| List price:
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£149.99 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
1441923195 |
| ISBN 13: |
9781441923196 |
| Publisher: |
SPRINGER-VERLAG NEW YORK INC. |
| Pub. date: |
19 October, 2010 |
| Edition: |
Softcover reprint of hardcover 1st ed. 2005 |
| Series: |
Springer Series in Statistics |
| Pages: |
653 |
| Description: |
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. The book builds on recent developments, both at the foundational level and the computational level, to present a self-contained view. |
| Synopsis: |
This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view. |
| Illustrations: |
XVII, 653 p. |
| Publication: |
US |
| Imprint: |
Springer-Verlag New York Inc. |
| Returns: |
Returnable |
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