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Stochastic Approximation and Recursive Algorithms and Applications

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Release : 2006-05-04
Genre : Mathematics
Kind : eBook
Book Rating : 69X/5 ( reviews)

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Book Synopsis Stochastic Approximation and Recursive Algorithms and Applications by : Harold Kushner

Download or read book Stochastic Approximation and Recursive Algorithms and Applications written by Harold Kushner. This book was released on 2006-05-04. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Stochastic Approximation and Recursive Algorithms and Applications

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Author :
Release : 2014-01-15
Genre :
Kind : eBook
Book Rating : 975/5 ( reviews)

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Book Synopsis Stochastic Approximation and Recursive Algorithms and Applications by : Harold Kushner

Download or read book Stochastic Approximation and Recursive Algorithms and Applications written by Harold Kushner. This book was released on 2014-01-15. Available in PDF, EPUB and Kindle. Book excerpt:

Stochastic Recursive Algorithms for Optimization

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Author :
Release : 2012-08-11
Genre : Technology & Engineering
Kind : eBook
Book Rating : 853/5 ( reviews)

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Book Synopsis Stochastic Recursive Algorithms for Optimization by : S. Bhatnagar

Download or read book Stochastic Recursive Algorithms for Optimization written by S. Bhatnagar. This book was released on 2012-08-11. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms: • are easily implemented; • do not require an explicit system model; and • work with real or simulated data. Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix. The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from similarly diverse backgrounds: workers in relevant areas of computer science, control engineering, management science, applied mathematics, industrial engineering and operations research will find the content of value.

Stochastic Approximation Algorithms and Applications

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Author :
Release : 1997
Genre : Stochastic approximation
Kind : eBook
Book Rating : 982/5 ( reviews)

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Book Synopsis Stochastic Approximation Algorithms and Applications by :

Download or read book Stochastic Approximation Algorithms and Applications written by . This book was released on 1997. Available in PDF, EPUB and Kindle. Book excerpt: There is a thorough treatment of rate of convergence, iterate averaging, high-dimensional problems, ergodic cost problems, stability methods for correlated noise, and decentralized and asynchronous algorithms.

Stochastic Approximation and Recursive Algorithms and Applications

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Author :
Release : 2013-11-11
Genre : Mathematics
Kind : eBook
Book Rating : 968/5 ( reviews)

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Book Synopsis Stochastic Approximation and Recursive Algorithms and Applications by : Harold Kushner

Download or read book Stochastic Approximation and Recursive Algorithms and Applications written by Harold Kushner. This book was released on 2013-11-11. Available in PDF, EPUB and Kindle. Book excerpt: The most comprehensive and thorough treatment of modern stochastic approximation type algorithms to date, based on powerful methods connected with that of the ODE. It covers general constrained and unconstrained problems, w.p.1 as well as the very successful weak convergence methods under weak conditions on the dynamics and noise processes, asymptotic properties and rates of convergence, iterate averaging methods, ergodic cost problems, state dependent noise, high dimensional problems, plus decentralized and asynchronous algorithms, and the use of methods of large deviations. Examples from many fields illustrate and motivate the techniques.

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