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 ref. del art�culo V9780387943640

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Detalles bibliogr�ficos

T�tulo: Hidden Markov Models: Estimation and Control (Volume 29)
Editor: Springer/Sci-Tech/Trade
Fecha de publicaci�n: 1994
Idioma: Ingl�s
ISBN 10: 0387943641
ISBN 13: 9780387943640
Encuadernaci�n: Encuadernaci�n de tapa dura
Edici�n: 1� Edici�n
Estado: New

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Sinopsis

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.

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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.

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