Franklin

Hidden Markov models and dynamical systems [electronic resource] / Andrew M. Fraser.

Author/Creator:
Fraser, Andrew M.
Publication:
Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 2008.
Format/Description:
Book
1 online resource (xii, 132 p. ) ill. ;
Status/Location:
Loading...

Options
Location Notes Your Loan Policy

Details

Subjects:
Markov processes.
Dynamics.
Language:
English
System Details:
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Summary:
This text provides an introduction to hidden Markov models (HMMs) for the dynamical systems community. It is a valuable text for third or fourth year undergraduates studying engineering, mathematics, or science that includes work in probability, linear algebra and differential equations. The book presents algorithms for using HMMs, and it explains the derivation of those algorithms. It presents Kalman filtering as the extension to a continuous state space of a basic HMM algorithm. The book concludes with an application to biomedical signals. This text is distinctive for providing essential introductory material as well as presenting enough of the theory behind the basic algorithms so that the reader can use it as a guide to developing their own variants.
Contents:
1. Introduction
2. Basic algorithms
3. Variants and generalizations
4. Continuous states and observations and Kalman filtering
5. Performance bounds and a toy problem
6. Obstructive sleep apnea.
Notes:
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references (p. 125-129) and index.
Description based on title page of print version.
Contributor:
Society for Industrial and Applied Mathematics.
ISBN:
0-89871-774-4
Publisher Number:
OT107 siam
Access Restriction:
Restricted to subscribers or individual electronic text purchasers.