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Stochastic Networks (Paperback, Softcover reprint of the original 1st ed. 1995): Frank P. Kelly, Ruth J. Williams Stochastic Networks (Paperback, Softcover reprint of the original 1st ed. 1995)
Frank P. Kelly, Ruth J. Williams
R1,609 Discovery Miles 16 090 Ships in 10 - 15 working days

This IMA Volume in Mathematics and its Applications STOCHASTIC NETWORKS is based on the proceedings of a workshop that was an integral part of the 1993-94 IMA program on "Emerging Applications of Probability." We thank Frank P. Kelly and Ruth J. Williams for organizing the workshop and for editing the proceedings. We also take this opportunity to thank the National Science Foundation, the Air Force Office of Scientific Research, the Army Research Office, and the National Security Agency, whose financial support made the workshop possible. A vner Friedman Willard Miller, Jr. xiii PREFACE Research on stochastic networks has powerful driving applications in the modelling of manufacturing, telecommunications, and computer sys tems. These various applications have raised common mathematical issues of some subtlety, and a notable feature of the workshop was the way in which experts in different areas such as operations research, systems science and engineering, and applied mathematics have been attacking important problems from different viewpoints.

Introduction to Stochastic Integration (Paperback, 2nd ed. 1990): Kai L. Chung, Ruth J. Williams Introduction to Stochastic Integration (Paperback, 2nd ed. 1990)
Kai L. Chung, Ruth J. Williams
R2,194 Discovery Miles 21 940 Ships in 10 - 15 working days

A highly readable introduction to stochastic integration and stochastic differential equations, this book combines developments of the basic theory with applications. It is written in a style suitable for the text of a graduate course in stochastic calculus, following a course in probability.

Using the modern approach, the stochastic integral is defined for predictable integrands and local martingales; then Ito s change of variable formula is developed for continuous martingales. Applications include a characterization of Brownian motion, Hermite polynomials of martingales, the Feynman-Kac functional and Schrodinger equation. For Brownian motion, the topics of local time, reflected Brownian motion, and time change are discussed.

New to the second edition are a discussion of the Cameron-Martin-Girsanov transformation and a final chapter which provides an introduction to stochastic differential equations, as well as many exercises for classroom use.

This book will be a valuable resource to all mathematicians, statisticians, economists, and engineers employing the modern tools of stochastic analysis.

"The text also proves that stochastic integration has made an important impact on mathematical progress over the last decades and that stochastic calculus has become one of the most powerful tools in modern probability theory. "

Journal of the American Statistical Association

" horizontal dagger separator] "

"An attractive text written in a] lean and precise style eminently readable. Especially pleasant are the care and attention devoted to details A very fine book. "

Mathematical Reviews"

Introduction to Stochastic Integration (Paperback, 2nd 2013 ed.): Kai L. Chung, Ruth J. Williams Introduction to Stochastic Integration (Paperback, 2nd 2013 ed.)
Kai L. Chung, Ruth J. Williams
R1,497 Discovery Miles 14 970 Out of stock

A highly readable introduction to stochastic integration and stochastic differential equations, this book combines developments of the basic theory with applications. It is written in a style suitable for the text of a graduate course in stochastic calculus, following a course in probability.

Using the modern approach, the stochastic integral is defined for predictable integrands and local martingales; then Ito s change of variable formula is developed for continuous martingales. Applications include a characterization of Brownian motion, Hermite polynomials of martingales, the Feynman-Kac functional and Schrodinger equation. For Brownian motion, the topics of local time, reflected Brownian motion, and time change are discussed.

New to the second edition are a discussion of the Cameron-Martin-Girsanov transformation and a final chapter which provides an introduction to stochastic differential equations, as well as many exercises for classroom use.

This book will be a valuable resource to all mathematicians, statisticians, economists, and engineers employing the modern tools of stochastic analysis.

"The text also proves that stochastic integration has made an important impact on mathematical progress over the last decades and that stochastic calculus has become one of the most powerful tools in modern probability theory. "

Journal of the American Statistical Association

" horizontal dagger separator] "

"An attractive text written in a] lean and precise style eminently readable. Especially pleasant are the care and attention devoted to details A very fine book. "

Mathematical Reviews

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