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Theory of Markov Processes


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Автор: Dynkin E.
Название:  Theory of Markov Processes
Перевод названия: Дынкин: Теория процессов Маркова
ISBN: 9780486453057
Издательство: Dover
Классификация:
ISBN-10: 0486453057
Обложка/Формат: Paperback
Страницы: 224
Вес: 0.25 кг.
Дата издания: 06.10.2006
Серия: Dover books on mathematics
Язык: English
Размер: 141 x 214 x 18
Читательская аудитория: General (US: Trade)
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Поставляется из: США
Описание: An investigation of the logical foundations of the theory behind Markov random processes, this text explores subprocesses, transition functions, and conditions for boundedness and continuity. Rather than focusing on probability measures individually, the work explores connections between functions. An elementary grasp of the theory of Markov processes is assumed.
Starting with a brief survey of relevant concepts and theorems from measure theory, the text investigates operations that permit an inspection of the class of Markov processes corresponding to a given transition function. It advances to the more complicated operations of generating a subprocess, followed by examinations of the construction of Markov processes with given transition functions, the concept of a strictly Markov process, and the conditions required for boundedness and continuity of a Markov process. Addenda, notes, references, and indexes supplement the text.



Introduction to Stochastic Processes

Автор: Cinlar, Erhan
Название: Introduction to Stochastic Processes
ISBN: 0486497976 ISBN-13(EAN): 9780486497976
Издательство: Dover
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Цена: 4343.00 р.
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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.


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