Probability Random Variables And Random Processes
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Schaum's Outline of Probability, Random Variables, and Random Processes, 3/E (Enhanced Ebook)
Author: Hwei P. Hsu
language: en
Publisher: McGraw Hill Professional
Release Date: 2014-03-14
The ideal review for the thousands of electrical engineering college students who enroll in probability, variables, and processes courses Schaum's Outline of Probability, Random Variables, and Random Processes mirrors the courses in scope and sequence to help enrolled students understand basic concepts and offer extra practice on topics such as bivariate random variables, joint distribution functions, moment generating functions, Poisson processes, Wiener processes, power spectral densities, and white noise. Coverage will also include response of linear systems to random outputs, Fourier series and Karhunen-Loeve expansions, Fourier transform of random processes, parameter estimation, Bayes' estimation, and mean square estimation. Features Outline format supplies a concise guide to the standard college courses in probability, variables, and processes 405 solved problems New chapter on statistical communication theory Additional material on distributions, the Markov Process, and martingales Supports all the major textbooks for probability, variables, and processes courses
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.
Introduction to Probability, Statistics, and Random Processes
The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities; limit theorems and convergence; introduction to Bayesian and classical statistics; random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion; simulation using MATLAB and R.