Introduction to Probability Theory and Stochastic Processes

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  • Format: Hardcover
  • Copyright: 2013-04-08
  • Publisher: Wiley

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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.

Author Biography

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.

Table of Contents

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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