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eBook Stochastic Approximation (Cambridge Tracts in Mathematics) download
Science
Author: M. T. Wasan
ISBN: 0521604850
Subcategory: Mathematics
Pages 216 pages
Publisher Cambridge University Press; Revised ed. edition (June 3, 2004)
Language English
Category: Science
Rating: 4.8
Votes: 722
ePUB size: 1872 kb
FB2 size: 1133 kb
DJVU size: 1504 kb
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eBook Stochastic Approximation (Cambridge Tracts in Mathematics) download

by M. T. Wasan


Series: Cambridge Tracts in Mathematics (Book 58).

Stochastic approximation is a technique for studying the properties of an experimental situation; it has important applications in fields such as medicine and engineering. Dr Wasan gives a rigorous mathematical treatment of the subject. The discussion and proofs of theorems are easy to follow, while a number of interesting examples show how the techniques may be applied in many fields. Series: Cambridge Tracts in Mathematics (Book 58). Paperback: 216 pages.

Cambridge Tracts in Mathematics. Download list of titles. Other actions Stochastic systems provide powerful abstract models for a variety of important real-life applications: for example, power supply, traffic. About Cambridge Tracts in Mathematics. The material is presented in such a way that it guides the reader smoothly and intuitively through the process, leading to a deeper understanding of the topic. Applications of Diophantine Approximation to Integral Points and Transcendence. Stochastic systems provide powerful abstract models for a variety of important real-life applications: for example, power supply, traffic flow, data transmission.

Stochastic approximation. by. Wasan, M. T. Publication date. London, Cambridge . inlibrary; printdisabled; ; china.

Stochastic Approximation book. Stochastic Approximation (Cambridge Tracts in Mathematics). 0521073685 (ISBN13: 9780521073684). In this book, Dr Wasan gives a rigorous mathematical treatment of the subject, drawing together the scattered results of a number of authors. He discusses the conditions under which the method gives a valid approximation to the required solution; methods for optimal choice of parameters to hasten convergence; the comparison of the method with other techniques.

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Stochastic Approximation M. Wasan Cambridge Academ . Wasan Cambridge Academ 9780521604857 : Stochastic approximation is a relatively new technique for studying the properties of an experimental situation; it has i.

A method for solving a class of problems of statistical estimation, in which the new value of the estimator is a modification of an existing estimator, based on new information. The first procedure of stochastic approximation was proposed in 1951 by H. Robbins and S. Monro. Let every measurement of a function,, at a point contain a random error with mean zero. The Robbins–Monro procedure of stochastic approximation for finding a root of the equation takes the form.

Quantum Stochastic Processes and Noncommutative Geometry (Cambridge Tracts in Mathematics). Quantum Stochastic Processes and Noncommutative Geometry (Cambridge Tracts in Mathematics). Kalyan B. Sinha, Debashish Goswami, Download (pdf, . 6 Mb) Donate Read. Epub FB2 mobi txt RTF. Converted file can differ from the original. If possible, download the file in its original format.

Cambridge Tracts in Mathematics (Paperback). Cambridge University Press.

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95), isbn 0 521 43275 8 (Cambridge University Press, 1999). 95), isbn 0 521 43275 8 (Cambridge University Press, 1999). Do you want to read the rest of this article? Request full-text.

Stochastic approximation is a relatively new technique for studying the properties of an experimental situation; it has important applications in fields such as medicine and engineering. The subject can be treated either largely as a branch of pure mathematics, or else from an empirical and practical angle. In this book, Dr Wasan gives a rigorous mathematical treatment of the subject, drawing together the scattered results of a number of authors. He discusses the conditions under which the method gives a valid approximation to the required solution; methods for optimal choice of parameters to hasten convergence; the comparison of the method with other techniques. The discussion and proofs of theorems are given in enough detail to make them easy to follow, while a number of interesting examples show how the techniques may be applied in many fields.