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＜電子ブック＞
Basics of Probability and Stochastic Processes / by Esra Bas

版	1st ed. 2019.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2019
本文言語	英語
大きさ	IX, 307 p : online resource
著者標目	*Bas, Esra author SpringerLink (Online service)
件　名	LCSH:Markov processes LCSH:Engineering mathematics LCSH:Discrete mathematics LCSH:Security systems FREE:Markov Process FREE:Engineering Mathematics FREE:Discrete Mathematics FREE:Security Science and Technology
一般注記	Combinatorial Analysis -- Basic Concepts in Probability -- Conditional Probability, Bayes’s Formula, Independent Events -- Introduction to Random Variables -- Discrete Random Variables -- Continuous Random Variables -- Other Selected Topics in Basic Probability -- A Brief Introduction to Stochastic Processes -- A Brief Introduction to Point Process, Counting Process, Renewal Process, Regenerative Process, Poisson Process -- Poisson Process -- Renewal Process -- An Introduction to Markov Chains -- Special Discrete-Time Markov Chains -- Continuous-Time Markov Chains -- An Introduction to Queueing Models -- Introduction to Brownian Motion -- Basics of Martingales -- Basics of Reliability Theory This textbook explores probability and stochastic processes at a level that does not require any prior knowledge except basic calculus. It presents the fundamental concepts in a step-by-step manner, and offers remarks and warnings for deeper insights. The chapters include basic examples, which are revisited as the new concepts are introduced. To aid learning, figures and diagrams are used to help readers grasp the concepts, and the solutions to the exercises and problems. Further, a table format is also used where relevant for better comparison of the ideas and formulae. The first part of the book introduces readers to the essentials of probability, including combinatorial analysis, conditional probability, and discrete and continuous random variable. The second part then covers fundamental stochastic processes, including point, counting, renewal and regenerative processes, the Poisson process, Markov chains, queuing models and reliability theory. Primarily intended for undergraduate engineering students, it is also useful for graduate-level students wanting to refresh their knowledge of the basics of probability and stochastic processes HTTP:URL=https://doi.org/10.1007/978-3-030-32323-3

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