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Hidden Markov Models and Dynamical Systems

Autor Andrew M. Fraser
en Limba Engleză Paperback – 19 mar 2009
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.
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Specificații

ISBN-13: 9780898716658
ISBN-10: 0898716659
Pagini: 143
Ilustrații: Illustrations
Dimensiuni: 174 x 247 x 7 mm
Greutate: 0 kg
Ediția:New.
Editura: Society for Industrial and Applied Mathematics
Colecția Society for Industrial and Applied Mathematics
Locul publicării:Philadelphia, United States

Cuprins

Preface; 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; Appendix A. Formulas for matrices and Gaussians; Appendix B. Notes on software; Bibliography; Index.

Notă biografică


Descriere

Presents algorithms for using HMMs and explains the derivation of those algorithms for the dynamical systems community.