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- catalog abstract "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.".
- catalog contributor b13050585.
- catalog contributor b13050586.
- catalog contributor b13050587.
- catalog created "2003.".
- catalog date "2003".
- catalog date "2003.".
- catalog dateCopyrighted "2003.".
- catalog description "Includes bibliographical references (pages 443-463) and indexes.".
- catalog description "Introduction: Applications and Issues -- Applications to Learning, Repeated Games, State Dependent Noise, and Queue Optimization -- Applications to Signal Processing, Communications, and Adaptive Control -- Mathematical Background -- Convergence w.p.1: Martingale Difference Noise -- Convergence w.p.1: Correlated Noise -- Weak Convergence: Introduction -- Weak Convergence Methods for General Algorithms -- Applications: Proofs of Convergence -- Rate of Convergence -- Averaging of the Iterates -- Distributed/Decentralized and Asynchronous Algorithms.".
- catalog description "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.".
- catalog extent "xxii, 474 p. :".
- catalog identifier "0387008942 (acid-free paper)".
- catalog isPartOf "Applications of mathematics ; 35".
- catalog issued "2003".
- catalog issued "2003.".
- catalog language "eng".
- catalog publisher "Berlin ; New York : Springer,".
- catalog subject "519.2 21".
- catalog subject "Algorithms.".
- catalog subject "Distribution (Probability theory).".
- catalog subject "Mathematics.".
- catalog subject "QA274.2 .K88 2003".
- catalog subject "Recursive functions.".
- catalog subject "Stochastic approximation.".
- catalog tableOfContents "Introduction: Applications and Issues -- Applications to Learning, Repeated Games, State Dependent Noise, and Queue Optimization -- Applications to Signal Processing, Communications, and Adaptive Control -- Mathematical Background -- Convergence w.p.1: Martingale Difference Noise -- Convergence w.p.1: Correlated Noise -- Weak Convergence: Introduction -- Weak Convergence Methods for General Algorithms -- Applications: Proofs of Convergence -- Rate of Convergence -- Averaging of the Iterates -- Distributed/Decentralized and Asynchronous Algorithms.".
- catalog title "Stochastic approximation and recursive algorithms and applications / Harold J. Kushner, G. George Yin.".
- catalog type "text".