Probability, Statistics, and Random Processes for Electrical EngineeringThis is the standard textbook for courses on probability and statistics, not substantially updated. While helping students to develop their problemsolving 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 workedout realworld examples. In this edition, the Computer Methods sections have been updated and substantially enhanced and new problems have been added. 
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Completely Unsuitable as an Undergrad Text. Use Schaums Outlines
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Contents
Probability Models in Electrical  1 
Basic Concepts of Probability Theory  21 
Discrete Random Variables  96 
Copyright  
11 other sections not shown
Other editions  View all
Probability, Statistics, and Random Processes For Electrical Engineering Alberto LeonGarcia No preview available  2011 
Probability, Statistics, and Random Processes for Electrical Engineering Alberto LeonGarcia No preview available  2008 
Common terms and phrases
arrival rate autocorrelation function autocovariance average ball Bernoulli trials binary characteristic function confidence intervals continuoustime converge corresponding covariance matrix defined discrete random variable discretetime 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 widesense stationary Wiener process zero zeromean