Автор: Cinlar, Erhan Название: Introduction to Stochastic Processes ISBN: 0486497976 ISBN-13(EAN): 9780486497976 Издательство: Dover Рейтинг: Цена: 2112 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This clear presentation of the most fundamental models of random phenomena employs methods that recognize computer-related aspects of theory. The text emphasizes the modern viewpoint, in which the primary concern is the behavior of sample paths. By employing matrix algebra and recursive methods, rather than transform methods, it provides techniques readily adaptable to computing with machines. Topics include probability spaces and random variables, expectations and independence, Bernoulli processes and sums of independent random variables, Poisson processes, Markov chains and processes, and renewal theory. Assuming some background in calculus but none in measure theory, the complete, detailed, and well-written treatment is suitable for engineering students in applied mathematics and operations research courses as well as those in a wide variety of other scientific fields. Many numerical examples, worked out in detail, appear throughout the text, in addition to numerous end-of-chapter exercises and answers to selected exercises.
Автор: Astrom Karl Название: Introduction to Stochastic Control Theory ISBN: 0486445313 ISBN-13(EAN): 9780486445311 Издательство: Dover Рейтинг: Цена: 1407 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text for upper-level undergraduates and graduate students explores stochastic control theory in terms of analysis, parametric optimization, and optimal stochastic control. Limited to linear systems with quadratic criteria, it covers discrete time as well as continuous time systems. 1970 edition.
Описание: Considerable research has been devoted to the formulation and solution of problems involving flow within connected networks. Independent of these surveys, an extensive body of knowledge has accumulated on the subject of queues, particularly in regard to stochastic flow through single-node servicing facilities. This text combines studies of connected networks with those of stochastic flow, providing a basis for understanding the general behavior and operation of communication networks in realistic situations. Author Leonard Kleinrock of the Computer Science Department at UCLA created the basic principle of packet switching, the technology underpinning the Internet. In this text, he develops a queuing theory model of communications nets. Its networks are channel-capacity limited; consequently, the measure of performance is taken to be the average delay encountered by a message in passing through the net. Topics include questions pertaining to optimal channel capacity assignment, effect of priority and other queue disciplines, choice of routine procedure, fixed-cost restraint, and design of topological structures. Many separate facets are brought into focus in the concluding discussion of the simulation of communication nets, and six appendices offer valuable supplementary information.
Описание: Two-part treatment begins with a self-contained introduction to the subject, followed by applications to stochastic analysis and mathematical physics. "A welcome addition." - Bulletin of the American Mathematical Society. 1986 edition.
Автор: Rao M. Название: Foundations of Stochastic Analysis ISBN: 0486481220 ISBN-13(EAN): 9780486481227 Издательство: Dover Рейтинг: Цена: 1799 р. Наличие на складе: Поставка под заказ.
Описание: Stochastic analysis involves the study of a process involving a randomly determined sequence of observations, each of which represents a sample of one element of probability distribution. This volume considers fundamental theories and contrasts the natural interplay between real and abstract methods. Starting with the introduction of the basic Kolmogorov-Bochner existence theorem, the text explores conditional expectations and probabilities as well as projective and direct limits. Subsequent chapters examine several aspects of discrete martingale theory, including applications to ergodic theory, likelihood ratios, and the Gaussian dichotomy theorem. Prerequisites include a standard measure theory course. No prior knowledge of probability is assumed; therefore, most of the results are proved in detail. Each chapter concludes with a problem section that features many hints and facts, including the most important results in information theory.
Автор: Jazwinski Andrew Название: Stochastic Processes and Filtering Theory ISBN: 0486462749 ISBN-13(EAN): 9780486462745 Издательство: Dover Рейтинг: Цена: 1955 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well. Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.
Описание: The first of a two-volume set begins with discussions of stochastic processes, including posterity analysis, birth-and-death processes, renewal theory, renewal-reward and regenerative processes, Markov chains, continuous-time Markov chains, Markov processes, and stationery processes and ergodic theory. Its coverage of operating characteristics of stochastic systems examines system properties, networks of queues, and bounds and approximations. This two-volume set of texts explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. They demonstrate the interdependence of three areas of study that usually receive separate treatments: stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, this work emphasizes the practical importance, intellectual stimulation, and mathematical elegance of stochastic models. It is intended primarily as a graduate-level text for studies in operations research, management science, computer science, and all branches of engineering, applied mathematics, statistics, and economics.