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An Introduction to Probability and Stochastic Processes

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Release : 2013-01-01
Genre : Mathematics
Kind : eBook
Book Rating : 998/5 ( reviews)

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Book Synopsis An Introduction to Probability and Stochastic Processes by : James L. Melsa

Download or read book An Introduction to Probability and Stochastic Processes written by James L. Melsa. This book was released on 2013-01-01. Available in PDF, EPUB and Kindle. Book excerpt: Detailed coverage of probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

An Introduction to Probability and Stochastic Processes

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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 267/5 ( reviews)

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Book Synopsis An Introduction to Probability and Stochastic Processes by : Marc A. Berger

Download or read book An Introduction to Probability and Stochastic Processes written by Marc A. Berger. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: These notes were written as a result of my having taught a "nonmeasure theoretic" course in probability and stochastic processes a few times at the Weizmann Institute in Israel. I have tried to follow two principles. The first is to prove things "probabilistically" whenever possible without recourse to other branches of mathematics and in a notation that is as "probabilistic" as possible. Thus, for example, the asymptotics of pn for large n, where P is a stochastic matrix, is developed in Section V by using passage probabilities and hitting times rather than, say, pulling in Perron Frobenius theory or spectral analysis. Similarly in Section II the joint normal distribution is studied through conditional expectation rather than quadratic forms. The second principle I have tried to follow is to only prove results in their simple forms and to try to eliminate any minor technical com putations from proofs, so as to expose the most important steps. Steps in proofs or derivations that involve algebra or basic calculus are not shown; only steps involving, say, the use of independence or a dominated convergence argument or an assumptjon in a theorem are displayed. For example, in proving inversion formulas for characteristic functions I omit steps involving evaluation of basic trigonometric integrals and display details only where use is made of Fubini's Theorem or the Dominated Convergence Theorem.

Introduction to Probability and Stochastic Processes with Applications

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Release : 2014-08-21
Genre : Mathematics
Kind : eBook
Book Rating : 960/5 ( reviews)

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Book Synopsis Introduction to Probability and Stochastic Processes with Applications by : Liliana Blanco Castañeda

Download or read book Introduction to Probability and Stochastic Processes with Applications written by Liliana Blanco Castañeda. This book was released on 2014-08-21. Available in PDF, EPUB and Kindle. Book excerpt: An easily accessible, real-world approach to probability and stochastic processes Introduction to Probability and Stochastic Processes with Applications presents a clear, easy-to-understand treatment of probability and stochastic processes, providing readers with a solid foundation they can build upon throughout their careers. With an emphasis on applications in engineering, applied sciences, business and finance, statistics, mathematics, and operations research, the book features numerous real-world examples that illustrate how random phenomena occur in nature and how to use probabilistic techniques to accurately model these phenomena. The authors discuss a broad range of topics, from the basic concepts of probability to advanced topics for further study, including Itô integrals, martingales, and sigma algebras. Additional topical coverage includes: Distributions of discrete and continuous random variables frequently used in applications Random vectors, conditional probability, expectation, and multivariate normal distributions The laws of large numbers, limit theorems, and convergence of sequences of random variables Stochastic processes and related applications, particularly in queueing systems Financial mathematics, including pricing methods such as risk-neutral valuation and the Black-Scholes formula Extensive appendices containing a review of the requisite mathematics and tables of standard distributions for use in applications are provided, and plentiful exercises, problems, and solutions are found throughout. Also, a related website features additional exercises with solutions and supplementary material for classroom use. Introduction to Probability and Stochastic Processes with Applications is an ideal book for probability courses at the upper-undergraduate level. The book is also a valuable reference for researchers and practitioners in the fields of engineering, operations research, and computer science who conduct data analysis to make decisions in their everyday work.

Probability and Stochastic Processes

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Release : 2014-01-28
Genre : Mathematics
Kind : eBook
Book Rating : 560/5 ( reviews)

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Book Synopsis Probability and Stochastic Processes by : Roy D. Yates

Download or read book Probability and Stochastic Processes written by Roy D. Yates. This book was released on 2014-01-28. Available in PDF, EPUB and Kindle. Book excerpt: This text introduces engineering students to probability theory and stochastic processes. Along with thorough mathematical development of the subject, the book presents intuitive explanations of key points in order to give students the insights they need to apply math to practical engineering problems. The first seven chapters contain the core material that is essential to any introductory course. In one-semester undergraduate courses, instructors can select material from the remaining chapters to meet their individual goals. Graduate courses can cover all chapters in one semester.

Introduction to Probability Theory and Stochastic Processes

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Author :
Release : 2013-04-08
Genre : Mathematics
Kind : eBook
Book Rating : 79X/5 ( reviews)

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Book Synopsis Introduction to Probability Theory and Stochastic Processes by : John Chiasson

Download or read book Introduction to Probability Theory and Stochastic Processes written by John Chiasson. This book was released on 2013-04-08. Available in PDF, EPUB and Kindle. Book excerpt: A unique approach to stochastic processes that connects the mathematical formulation of random processes to their use in applications This book presents an innovative approach to teaching probability theory and stochastic processes based on the binary expansion of the unit interval. Departing from standard pedagogy, it uses the binary expansion of the unit interval to explicitly construct an infinite sequence of independent random variables (of any given distribution) on a single probability space. This construction then provides the framework to understand the mathematical formulation of probability theory for its use in applications. Features include: The theory is presented first for countable sample spaces (Chapters 1-3) and then for uncountable sample spaces (Chapters 4-18) Coverage of the explicit construction of i.i.d. random variables on a single probability space to explain why it is the distribution function rather than the functional form of random variables that matters when it comes to modeling random phenomena Explicit construction of continuous random variables to facilitate the "digestion" of random variables, i.e., how they are used in contrast to how they are defined Explicit construction of continuous random variables to facilitate the two views of expectation: as integration over the underlying probability space (abstract view) or as integration using the density function (usual view) A discussion of the connections between Bernoulli, geometric, and Poisson processes Incorporation of the Johnson-Nyquist noise model and an explanation of why (and when) it is valid to use a delta function to model its autocovariance Comprehensive, astute, and practical, Introduction to Probability Theory and Stochastic Processes is a clear presentation of essential topics for those studying communications, control, machine learning, digital signal processing, computer networks, pattern recognition, image processing, and coding theory.

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