Description: Inference in Hidden Markov Models Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Olivier Cappe, Eric Moulines, Tobias Ryden Format: Paperback Publisher: Springer-Verlag New York Inc., United States Imprint: Springer-Verlag New York Inc. ISBN-13: 9781441923196, 978-1441923196 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.
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Location: Aldershot
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Book Title: Inference in Hidden Markov Models
Number of Pages: 653 Pages
Language: English
Publication Name: Inference in Hidden Markov Models
Publisher: Springer-Verlag New York Inc.
Publication Year: 2010
Subject: Engineering & Technology, Government, Computer Science, Mathematics
Item Height: 235 mm
Item Weight: 1015 g
Type: Textbook
Author: Tobias Ryden, Eric Moulines, Olivier Cappe
Series: Springer Series in Statistics
Item Width: 155 mm
Format: Paperback
