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Hidden Markov Models and Dynamical Systems
Andrew M. Fraser
€ 94.77
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Description for Hidden Markov Models and Dynamical Systems
Paperback. Presents algorithms for using HMMs and explains the derivation of those algorithms for the dynamical systems community. Num Pages: 143 pages, Illustrations. BIC Classification: PBW. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 253 x 144 x 10. Weight in Grams: 274. 143 pages, Illustrations. Presents algorithms for using HMMs and explains the derivation of those algorithms for the dynamical systems community. Cateogry: (P) Professional & Vocational; (U) Tertiary Education (US: College). BIC Classification: PBW. Dimension: 253 x 144 x 10. Weight: 272.
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 ... Read more
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 ... Read more
Product Details
Format
Paperback
Publication date
2008
Publisher
Society for Industrial and Applied Mathematics
Number of pages
143
Condition
New
Number of Pages
143
Place of Publication
New York, United States
ISBN
9780898716658
SKU
V9780898716658
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-1
About Andrew M. Fraser
Andrew M. Fraser is a Technical Staff Member in the ISR division of the Los Alamos National Laboratory where he uses stochastic models in his work on signal analysis. He spent 15 years at Portland State University in Oregon serving on the faculties of both the Systems Science PhD Program and the Electrical and Computer Engineering Department before joining LANL ... Read more
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