Solutions Manual for Probablistic Methods of Signal and System Analysis

Solutions Manual for Probablistic Methods of Signal and System Analysis

Author: George R. Cooper

Publisher: Oxford University Press, USA

Published: 1998-08-01

Total Pages: 124

ISBN-13: 9780195123555

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This Solutions Manual is intended to accompany Probabilistic Methods of Signal and System Analysis, Third Edition by George R. Cooper and Clare D. McGillem. It contains fully worked-out solutions to problems in the main text. The manual is available free to adopters of the main text.


Probabilistic Methods of Signal and System Analysis

Probabilistic Methods of Signal and System Analysis

Author: George R. Cooper

Publisher: Oxford Series in Electrical an

Published: 1999

Total Pages: 480

ISBN-13: 9780195123548

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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.


Probability and Stochastic Processes

Probability and Stochastic Processes

Author: Roy D. Yates

Publisher: John Wiley & Sons

Published: 2014-01-28

Total Pages: 514

ISBN-13: 1118324560

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This text introduces engineering students to probability theory and stochastic processes. Along with thorough mathematical development of the subject, the book presents intuitive explanations of key points in order to give students the insights they need to apply math to practical engineering problems. The first five chapters contain the core material that is essential to any introductory course. In one-semester undergraduate courses, instructors can select material from the remaining chapters to meet their individual goals. Graduate courses can cover all chapters in one semester.