Discrete Stochastic Processes And Applications


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Stochastic Processes


Stochastic Processes

Author: Robert G. Gallager

language: en

Publisher: Cambridge University Press

Release Date: 2013-12-12


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The definitive textbook on stochastic processes, written by one of the world's leading information theorists, covering both theory and applications.

Stochastic Processes with Applications


Stochastic Processes with Applications

Author: Rabi N. Bhattacharya

language: en

Publisher: SIAM

Release Date: 2009-08-27


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This book develops systematically and rigorously, yet in an expository and lively manner, the evolution of general random processes and their large time properties such as transience, recurrence, and convergence to steady states. The emphasis is on the most important classes of these processes from the viewpoint of theory as well as applications, namely, Markov processes. The book features very broad coverage of the most applicable aspects of stochastic processes, including sufficient material for self-contained courses on random walks in one and multiple dimensions; Markov chains in discrete and continuous times, including birth-death processes; Brownian motion and diffusions; stochastic optimization; and stochastic differential equations. This book is for graduate students in mathematics, statistics, science and engineering, and it may also be used as a reference by professionals in diverse fields whose work involves the application of probability.

Discrete Stochastic Processes


Discrete Stochastic Processes

Author: Robert G. Gallager

language: en

Publisher: Springer Science & Business Media

Release Date: 2012-12-06


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Stochastic processes are found in probabilistic systems that evolve with time. Discrete stochastic processes change by only integer time steps (for some time scale), or are characterized by discrete occurrences at arbitrary times. Discrete Stochastic Processes helps the reader develop the understanding and intuition necessary to apply stochastic process theory in engineering, science and operations research. The book approaches the subject via many simple examples which build insight into the structure of stochastic processes and the general effect of these phenomena in real systems. The book presents mathematical ideas without recourse to measure theory, using only minimal mathematical analysis. In the proofs and explanations, clarity is favored over formal rigor, and simplicity over generality. Numerous examples are given to show how results fail to hold when all the conditions are not satisfied. Audience: An excellent textbook for a graduate level course in engineering and operations research. Also an invaluable reference for all those requiring a deeper understanding of the subject.


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