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Num Pages: 396 pages, biography. BIC Classification: PBWL. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 22. Weight in Grams: 1610. . 1994. 1st ed. 1995. Corr. 3rd printing 2008. hardcover. . . . . N° de réf. du vendeur V9780387943640
The aim of this book is to present graduate students with a thorough survey of reference probability models and their applications to optimal estimation and control. These new and powerful methods are particularly useful in signal processing applications where signal models are only partially known and are in noisy environments. Well-known results, including Kalman filters and the Wonham filter, emerge as special cases. The authors begin with discrete time and discrete state spaces. From there, they proceed to cover continuous time, and progress from linear models to nonlinear models, and from completely known models to only partially known models. Readers are assumed to have a basic grounding in probability and systems theory, such as might be gained from the first year of graduate study, but otherwise this account is self-contained. Throughout, the authors have taken care to demonstrate engineering applications which show the usefulness of these methods.
Titre : Hidden Markov Models: Estimation and Control...
Éditeur : Springer/Sci-Tech/Trade
Date d'édition : 1994
Reliure : Couverture rigide
Etat : New
Edition : Edition originale
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control. As more applications are found, interest in Hidden Markov Models continues to grow. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780387943640
Quantité disponible : 1 disponible(s)
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Hardcover. Etat : new. Hardcover. As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control. As more applications are found, interest in Hidden Markov Models continues to grow. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9780387943640
Quantité disponible : 1 disponible(s)