Exploring Probability And Random Processes Using Matlab
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Exploring Probability and Random Processes Using MATLAB®
"Exploring Probability and Random Processes Using MATLAB®" offers a comprehensive guide to probability theory, stochastic processes, and their practical applications, focusing on intuitive understanding and MATLAB implementation. This book provides readers with a solid foundation in probability and stochastic processes while equipping them with tools and techniques for real-world scenarios. We begin with an introduction to probability theory, covering random variables, probability distributions, and statistical measures. Readers learn how to analyze and interpret uncertainty, make probabilistic predictions, and understand statistical inference principles. Moving on to stochastic processes, we explore discrete-time and continuous-time processes, Markov chains, and other key concepts. Practical examples and MATLAB code snippets illustrate essential concepts and demonstrate their implementation in MATLAB. One distinguishing feature is the emphasis on intuitive understanding and practical application. Complex mathematical concepts are explained clearly and accessibly, making the material approachable for readers with varying mathematical backgrounds. MATLAB examples provide hands-on experience and develop proficiency in using MATLAB for probability and stochastic processes analysis. Whether you're a student building a foundation in probability theory and stochastic processes, a researcher seeking practical data analysis tools, or a practitioner in engineering or finance, this book will provide the knowledge and skills needed to succeed. With a blend of theoretical insights and practical applications, "Exploring Probability and Random Processes Using MATLAB®" is an invaluable resource.
Intuitive Probability and Random Processes using MATLAB®
Author: Steven Kay
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-03-20
Intuitive Probability and Random Processes using MATLAB® is an introduction to probability and random processes that merges theory with practice. Based on the author’s belief that only "hands-on" experience with the material can promote intuitive understanding, the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have to study this?" Other salient features are: *heavy reliance on computer simulation for illustration and student exercises *the incorporation of MATLAB programs and code segments *discussion of discrete random variables followed by continuous random variables to minimize confusion *summary sections at the beginning of each chapter *in-line equation explanations *warnings on common errors and pitfalls *over 750 problems designed to help the reader assimilate and extend the concepts Intuitive Probability and Random Processes using MATLAB® is intended for undergraduate and first-year graduate students in engineering. The practicing engineer as well as others having the appropriate mathematical background will also benefit from this book. About the Author Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts..." from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.
Probability and Random Processes
Miller and Childers have focused on creating a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course. It is aimed at graduate students as well as practicing engineers, and includes unique chapters on narrowband random processes and simulation techniques. The appendices provide a refresher in such areas as linear algebra, set theory, random variables, and more. Probability and Random Processes also includes applications in digital communications, information theory, coding theory, image processing, speech analysis, synthesis and recognition, and other fields. * Exceptional exposition and numerous worked out problems make the book extremely readable and accessible * The authors connect the applications discussed in class to the textbook * The new edition contains more real world signal processing and communications applications * Includes an entire chapter devoted to simulation techniques.