Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability)

Kushner, Harold J.; Yin, G. George

ISBN 10: 1441918477 ISBN 13: 9781441918475

Edit� par Springer, 2010

Neuf(s) Couverture souple

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In English. N� de r�f. du vendeur ria9781441918475_new

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The book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. The assumptions and proof methods are designed to cover the needs of recent applications. The development proceeds from simple to complex problems, allowing the underlying ideas to be more easily understood. Many examples illustrate the application of the theory. This second edition is a thorough revision, although the main features and the structure remain unchanged. It contains many additional applications and results, and more detailed discussion.

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Titre : Stochastic Approximation and Recursive ...
�diteur : Springer
Date d'�dition : 2010
Reliure : Couverture souple
Etat : New
Edition : 2�me �dition

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Stochastic Approximation and Recursive Algorithms and Applications.

Kushner, Harold J.

Edit� par New York, NY, Springer New York., 2010

ISBN 10 : 1441918477 ISBN 13 : 9781441918475

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2., nd ed. Softcover version of original hardcover edition 2003. 235 mm x 155 mm, 744 g. XXII, 474 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband besto�en, daher M�ngelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stochastic Modelling and Applied Probability, 35. Sprache: Englisch. N� de r�f. du vendeur 2691LB

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Stochastic Approximation and Recursive Algorithms and Applications

G. George Yin

Edit� par Springer New York Nov 2010, 2010

ISBN 10 : 1441918477 ISBN 13 : 9781441918475

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as well as more detailed discussion. 500 pp. Englisch. N� de r�f. du vendeur 9781441918475

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Stochastic Approximation and Recursive Algorithms and Applications

Harold Kushner|G. George Yin

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ISBN 10 : 1441918477 ISBN 13 : 9781441918475

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and stru. N� de r�f. du vendeur 4172421

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Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability)

Kushner, Harold J.

Edit� par Springer, 2010

ISBN 10 : 1441918477 ISBN 13 : 9781441918475

Neuf Couverture souple

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Stochastic Approximation and Recursive Algorithms and Applications

Harold Kushner (u. a.)

Edit� par Springer, 2010

ISBN 10 : 1441918477 ISBN 13 : 9781441918475

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Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability)

Kushner, Harold J.; Yin, G. George

Edit� par Springer, 2010

ISBN 10 : 1441918477 ISBN 13 : 9781441918475

Neuf Couverture souple

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Etat : New. N� de r�f. du vendeur ABLIING23Mar2411530293679

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Stochastic Approximation and Recursive Algorithms and Applications

G. George Yin

Edit� par Springer New York, Springer US Nov 2010, 2010

ISBN 10 : 1441918477 ISBN 13 : 9781441918475

Neuf Taschenbuch

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The basic stochastic approximation algorithms introduced by Robbins and MonroandbyKieferandWolfowitzintheearly1950shavebeenthesubject of an enormous literature, both theoretical and applied. This is due to the large number of applications and the interesting theoretical issues in the analysis of �dynamically de ned� stochastic processes. The basic paradigm is a stochastic di erence equation such as = + Y , where takes n+1 n n n n its values in some Euclidean space, Y is a random variable, and the �step n size� > 0 is small and might go to zero as n . In its simplest form, n is a parameter of a system, and the random vector Y is a function of n �noise-corrupted� observations taken on the system when the parameter is set to . One recursively adjusts the parameter so that some goal is met n asymptotically. Thisbookisconcernedwiththequalitativeandasymptotic properties of such recursive algorithms in the diverse forms in which they arise in applications. There are analogous continuous time algorithms, but the conditions and proofs are generally very close to those for the discrete time case. The original work was motivated by the problem of nding a root of a continuous function g ( ), where the function is not known but the - perimenter is able to take �noisy� measurements at any desired value of . Recursive methods for root nding are common in classical numerical analysis, and it is reasonable to expect that appropriate stochastic analogs would also perform well.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 500 pp. Englisch. N� de r�f. du vendeur 9781441918475

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Stochastic Approximation and Recursive Algorithms and Applications

G. George Yin

Edit� par Springer New York, Springer US, 2010

ISBN 10 : 1441918477 ISBN 13 : 9781441918475

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The basic stochastic approximation algorithms introduced by Robbins and MonroandbyKieferandWolfowitzintheearly1950shavebeenthesubject of an enormous literature, both theoretical and applied. This is due to the large number of applications and the interesting theoretical issues in the analysis of 'dynamically de ned' stochastic processes. The basic paradigm is a stochastic di erence equation such as = + Y , where takes n+1 n n n n its values in some Euclidean space, Y is a random variable, and the 'step n size' > 0 is small and might go to zero as n . In its simplest form, n is a parameter of a system, and the random vector Y is a function of n 'noise-corrupted' observations taken on the system when the parameter is set to . One recursively adjusts the parameter so that some goal is met n asymptotically. Thisbookisconcernedwiththequalitativeandasymptotic properties of such recursive algorithms in the diverse forms in which they arise in applications. There are analogous continuous time algorithms, but the conditions and proofs are generally very close to those for the discrete time case. The original work was motivated by the problem of nding a root of a continuous function g ( ), where the function is not known but the - perimenter is able to take 'noisy' measurements at any desired value of . Recursive methods for root nding are common in classical numerical analysis, and it is reasonable to expect that appropriate stochastic analogs would also perform well. N� de r�f. du vendeur 9781441918475

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