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Pappband. Condition: Gut. 1st ed. 1995. Corr. 3rd printing 2008. Oktav Applications of Mathematics. Stochastic Modelling and Applied Probability, 29. 382 S. Orig.-Pappband. Gutes Exemplar.
Published by New York, Springer [1995]., 1995
ISBN 10: 0387943641 ISBN 13: 9780387943640
Language: English
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Add to basketHardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 60 ELL 9780387943640 Sprache: Englisch Gewicht in Gramm: 1150.
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Add to basketHardcover. corr. 3. print. 377 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. K00839 9780387943640 Sprache: Englisch Gewicht in Gramm: 1220.
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Published by Springer-Verlag New York Inc., New York, NY, 1994
ISBN 10: 0387943641 ISBN 13: 9780387943640
Language: English
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First Edition
Hardcover. Condition: 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.
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Add to basketGebunden. Condition: New. 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, i.
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Published by Springer New York Dez 1994, 1994
ISBN 10: 0387943641 ISBN 13: 9780387943640
Language: English
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Add to basketBuch. Condition: Neu. Neuware - 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.
Published by Springer-Verlag New York Inc., New York, NY, 1994
ISBN 10: 0387943641 ISBN 13: 9780387943640
Language: English
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First Edition
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Add to basketHardcover. Condition: 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.