Control and System Theory of Discrete-Time Stochastic Systems
Control and System Theory of Discrete-Time Stochastic Systems

Author: Jan H. van Schuppen

Publisher: Springer Nature

Published: 2021-08-02

Total Pages: 940

ISBN-13: 3030669521

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This book helps students, researchers, and practicing engineers to understand the theoretical framework of control and system theory for discrete-time stochastic systems so that they can then apply its principles to their own stochastic control systems and to the solution of control, filtering, and realization problems for such systems. Applications of the theory in the book include the control of ships, shock absorbers, traffic and communications networks, and power systems with fluctuating power flows. The focus of the book is a stochastic control system defined for a spectrum of probability distributions including Bernoulli, finite, Poisson, beta, gamma, and Gaussian distributions. The concepts of observability and controllability of a stochastic control system are defined and characterized. Each output process considered is, with respect to conditions, represented by a stochastic system called a stochastic realization. The existence of a control law is related to stochastic controllability while the existence of a filter system is related to stochastic observability. Stochastic control with partial observations is based on the existence of a stochastic realization of the filtration of the observed process.​

Encyclopaedia of Mathematics
Encyclopaedia of Mathematics

Author: Michiel Hazewinkel

Publisher: Springer Science & Business Media

Published: 1988

Total Pages: 620

ISBN-13: 9781556080050

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V.1. A-B v.2. C v.3. D-Feynman Measure. v.4. Fibonaccimethod H v.5. Lituus v.6. Lobachevskii Criterion (for Convergence)-Optical Sigman-Algebra. v.7. Orbi t-Rayleigh Equation. v.8. Reaction-Diffusion Equation-Stirling Interpolation Fo rmula. v.9. Stochastic Approximation-Zygmund Class of Functions. v.10. Subject Index-Author Index.

Stochastic Approximation and Recursive Algorithms and Applications
Stochastic Approximation and Recursive Algorithms and Applications

Author: Harold Kushner

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 432

ISBN-13: 1489926968

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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.

Heavy Traffic Analysis of Controlled Queueing and Communication Networks
Heavy Traffic Analysis of Controlled Queueing and Communication Networks

Author: Harold Kushner

Publisher: Springer Science & Business Media

Published: 2013-11-21

Total Pages: 522

ISBN-13: 1461300053

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One of the first books in the timely and important area of heavy traffic analysis of controlled and uncontrolled stochastics networks, by one of the leading authors in the field. The general theory is developed, with possibly state dependent parameters, and specialized to many different cases of practical interest.

Numerical Methods in Finance
Numerical Methods in Finance

Author: L. C. G. Rogers

Publisher: Cambridge University Press

Published: 1997-06-26

Total Pages: 348

ISBN-13: 9780521573542

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Numerical Methods in Finance describes a wide variety of numerical methods used in financial analysis.

Handbook of Computational and Numerical Methods in Finance
Handbook of Computational and Numerical Methods in Finance

Author: Svetlozar Todorov Rachev

Publisher: Springer Science & Business Media

Published: 2004-06-29

Total Pages: 456

ISBN-13: 9780817632199

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The subject of numerical methods in finance has recently emerged as a new discipline at the intersection of probability theory, finance, and numerical analysis. The methods employed bridge the gap between financial theory and computational practice, and provide solutions for complex problems that are difficult to solve by traditional analytical methods. Although numerical methods in finance have been studied intensively in recent years, many theoretical and practical financial aspects have yet to be explored. This volume presents current research and survey articles focusing on various numerical methods in finance. Key topics covered include: methodological issues, i.e., genetic algorithms, neural networks, Monte–Carlo methods, finite difference methods, stochastic portfolio optimization, as well as the application of other computational and numerical methods in finance and risk management. The book is designed for the academic community and will also serve professional investors. Contributors: K. Amir-Atefi; Z. Atakhanova; A. Biglova; O.J. Blaskowitz; D. D’Souza; W.K. Härdle; I. Huber; I. Khindanova; A. Kohatsu-Higa; P. Kokoszka; M. Montero; S. Ortobelli; E. Özturkmen; G. Pagès; A. Parfionovas; H. Pham; J. Printems; S. Rachev; B. Racheva-Jotova; F. Schlottmann; P. Schmidt; D. Seese; S. Stoyanov; C.E. Testuri; S. Trück; S. Uryasev; and Z. Zheng.