Probability, random variables, and random signal principles

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McGraw-Hill, 1980 - Mathematics - 267 pages
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Today, any well-designed electrical engineering curriculum must train engineers to account for noise and random signals in systems. The best approach is to emphasize fundamental principles since systems can vary greatly. Professor Peebles's book specifically has this emphasis, offering clear and concise coverage of the theories of probability, random variables, and random signals, including the response of linear networks to random waveforms. By careful organization, the book allows learning to flow naturally from the most elementary to the most advanced subjects. Time domain descriptions of the concepts are first introduced, followed by a thorough description of random signals using frequency domain. Practical applications are not forgotten, and the book includes discussions of practical noises (noise figures and noise temperatures) and an entire special chapter on applications of the theory. Another chapter is devoted to optimum networks when noise is present (matched filters and Wiener filters). This third edition differs from earlier editions mainly in making the book more useful for classroom use. Beside the addition of new topics (Poisson random processes, measurement of power spectra, and computer generation of random variables), the main change involves adding many new end-of-chapter exercises (180 were added for a total of over 800 exercises). The new exercises are all clearly identified for instructors who have used the previous edition.

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Contents

The Random Variable
33
Operations on One Random
60
Multiple Random Variables
77
Copyright

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About the author (1980)

PEYTON Z. PEEBLES, JR., is Professor Emeritus of Electrical and Computer Engineering at the University of Florida. His teaching, research, and industrial experience span three decades. Dr. Peebles has written more than fifty papers, mainly on radar-related topics, and a number of well-received textbooks, including Principles of Electrical Engineering; Digital Communication Systems; Probability, Random Variables, and Random Signal Principles; and Communication System Principles.