Probability, Statistics, and Random Processes for Electrical Engineering
This is the standard textbook for courses on probability and statistics, not substantially updated. While helping students to develop their problem-solving skills, the author motivates students with practical applications from various areas of ECE that demonstrate the relevance of probability theory to engineering practice. Included are chapter overviews, summaries, checklists of important terms, annotated references, and a wide selection of fully worked-out real-world examples. In this edition, the Computer Methods sections have been updated and substantially enhanced and new problems have been added.
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Probability Models in Electrical
Basic Concepts of Probability Theory
Discrete Random Variables
11 other sections not shown
arrival rate autocorrelation function autocovariance average ball Bernoulli trials binary characteristic function confidence intervals continuous-time converge corresponding covariance matrix defined discrete random variable discrete-time entropy equal equation estimator Example expected value exponential random variable exponentially distributed FIGURE filter Find the joint Find the mean Find the pdf Find the probability Gaussian random variables implies independent random variables input joint pdf jointly Gaussian random large number linear Markov chain mean and variance mean square error method number of customers obtain outcomes output packets Plot Poisson process Poisson random variable power spectral density Problem queueing system random experiment relative frequency result sample mean sample space Section server shown in Fig signal simulation Suppose theorem tosses transition probabilities uniform random variable variable with mean variable with parameter wide-sense stationary Wiener process zero zero-mean