Probability, random variables, and random signal principles (McGraw-Hill series in electrical engineering)

By Peyton Z. Peebles Jr.

Book Overview

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.

• Format: Hardcover
• Language: English
• ISBN: 0070491801
• ISBN13: 9780070491809
• Release Date: January 1980
• Publisher: Mcgraw-Hill,
• Length: 267 Pages
• Weight: 1.30 lbs.

Customer Reviews

4.5 stars as an undergraduate textbook for EE students

This book is one of the best undergradute textbooks for EE students, especially students having focus on physical-layer communication engineering. The highlight of this book is the enormous amount of well-written problems at the end of each chapter. These problems really help students fully understand abstract definitions and theorems which otherwise will not be easily cracked. This book, however, has the following drawbacks:1. The author should have emphasized in the first chapter the importance of real analysis and measure theory in order to motivate the students planning graduate research to study and prepare for the math courses during their undergraduate study. 2. No section for complex Gaussian random variable and vector, which are very important in digital communications.3. No limit theorems except CLT.4. No handling of convergence of a random sequence.Even with above drawbacks, this book is still the classic. I recommend ambitious students to read a little bit advanced books along with this book to better understand the subject.

A very good book for beginners.

I am a novice. I've been reading some other books of probability before, and I've found that this one is much clearer than the others.