Introduction to Probability Theory and Stochastic Processes
By: John Chiasson (author)Hardback
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This comprehensive textbook provides an introduction to statistical methods for graduate engineers offering thorough coverage of important probability-related topics to aid in product and system design, reliability engineering, quality control, and more. It introduces engineers to abstract concepts in mathematical stochastic processes and probability theory and covers topics such as coin tossing, simulation of random phenomena, brownian motion, white noise, and kalman filtering.
JOHN CHIASSON, PhD, is a Fellow of the IEEE and the author of Modeling and High-Performance Control of Electric Machines, published by Wiley-IEEE Press.
1 Coin Tossing 1 2 Countable Sample Spaces 61 3 Conditional Probability in Countable Sample Spaces 105 4 Uncountable Sample Spaces 151 5 Continuous Random Variables 213 6 Expectation 245 7 Modeling Random Phenomena 267 8 Functions of One Random Variables and Transforms 321 9 Functions of Two Random Variables 365 10 Two Functions of Two Random Variables 431 11 Conditional Probability for Continuous Random Variables 473 12 Random Vectors 549 13 Bernoulli, Geometric, and Poisson Processes 587 14 Brownian Motions and White Noise 645 15 Stationary Random Processes 703 16 Convergence of Random Variables 777 17 Statistics 839 18 Kalman Filter 905 Further Reading 933 Table of Common Distributions 935 References 941 Index 946
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- ID: 9781118382790
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