Probabilistic Methods of Signal and System Analysis

By Cordelia Moye

Probabilistic Methods of Signal and System Analysis, 3/e stresses the engineering applications of probability theory, presenting the material at a level and in a manner ideally suited to engineering students at the junior or senior level. It is also useful as a review for graduate students and practicing engineers.Thoroughly revised and updated, this third edition incorporates increased use of the computer in both text examples and selected problems. It utilizes MATLAB as a computational tool and includes new sections relating to Bernoulli trials, correlation of data sets, smoothing of data, computer computation of correlation functions and spectral densities, and computer simulation of systems. All computer examples can be run using the Student Version of MATLAB. Almost all of the examples and many of the problems have been modified or changed entirely, and a number of new problems have been added. A separate appendix discusses and illustrates the application of computers to signal and system analysis.

• Format: Hardcover
• Language: English
• ISBN: 0030706149
• ISBN13: 9780030706141
• Release Date: June 1995
• Publisher: Oxford University Press, USA
• Length: 432 Pages
• Weight: 1.54 lbs.
• Dimensions: 0.8" x 6.6" x 9.5"

Customer Reviews

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this is Amazing BOOK!!

I read this book several times and I can say that it is the best statistical & probability book for engineers or for computer scientist. My major is Image Processing (DSP, DIP, DVP) and reading this book helps me to increase my professional knowlege and rise my skills. I sincerelly recommend this book for any non-math major person. Now this book becomes desktop book for me like "Numercal Recipes in C" for any algorithm developer...

The ideal first book on random signal processing

As a professor in Electrical Engineering, I highly rate this book, describing it as the best text for an introductory course on prabability theory, statistics, random signals, and the analysis of systems with random signals as inputs. If you teach from this book, you can't go wrong!