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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Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.
This revised and expanded second edition presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. There is a complete development of both probability one and weak convergence methods for very general noise processes. The proofs of convergence use the ODE method, the most powerful to date. 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. Rate of convergence, iterate averaging, high-dimensional problems, stability-ODE methods, two time scale, asynchronous and decentralized algorithms, state-dependent noise, stability methods for correlated noise, perturbed test function methods, and large deviations methods are covered. Many motivating examples from learning theory, ergodic cost problems for discrete event systems, wireless communications, adaptive control, signal processing, and elsewhere illustrate the applications of the theory.
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Anbieter: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Deutschland
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 bestoßen, daher Mängelexemplar 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. Bestandsnummer des Verkäufers 2691LB
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9781441918475
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Zustand: 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. Bestandsnummer des Verkäufers 4172421
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Taschenbuch. Zustand: Neu. Stochastic Approximation and Recursive Algorithms and Applications | Harold Kushner (u. a.) | Taschenbuch | xxii | Englisch | 2010 | Springer | EAN 9781441918475 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Bestandsnummer des Verkäufers 107207865
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Zustand: New. pp. 500 2nd Edition. Bestandsnummer des Verkäufers 263091062
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9781441918475
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9781441918475
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Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Print on Demand pp. 500 31 Illus. Bestandsnummer des Verkäufers 5805481
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