Description Probability, Random Variables and Random Signal Principles offers clear and concise coverage of theories of probability, random variables, and random signals, including the response of linear networks to random waveforms for the junior-senior level course in electrical engineering. The book offers a careful, logical organization which stresses fundamentals and includes almost 900 student exercises and abundant practical applications for engineers to understand probability concepts.
The new edition sought to provide better integration of the material covering continuous and discrete time process, by presenting the material in parallel as much as possible. This should enable the student to better appreciate the similarities and differences between the same concepts when applied to continuous time and discrete time processes.
This edition features:
Digital Topics: Discussion on the continuous-time and discrete-time (DT) is clearly differentiated in Chapter 8. The discrete-time material retains the coverage of sampling theorems (baseband and bandpass) for random processes as a foundation for the DT material. Correlation functions and power spectrums for these processes, which are developed and connected through the sampling theorems and the DT Fourier transforms, are covered in Chapters 7 and 8, with some introduction in sections 6.1-6.3. The structure of linear DT digital systems is developed in both the sequence and transform domains.
Problems: End of chapter problems have been combined into a single list with numbering that corresponds to the chapter's section to which the problems mainly apply.
Starred sections: The level of coverage of the material is intended for a typical undergraduate program. However a small amount of more advanced material has been scattered throughout the book to serve as stimulation for the more advanced student or for schools using the book at a higher level. These sections are indicated by a star (*).
MATLAB-based examples and problems: They have been integrated into the text in key places (indicated by a computer icon).
New To This Edition
The discussions of complex valued random variables and random processes in Chapters 5-7 have been updated to include a description of the pseudo-variance and pseudo-covariance.
Chapter 6 was reorganized to separate the discussions of the concepts of distributions and moments, stationarity, and ergodicity into separate sections, and reordered the presentation.
In Chapter 7, the coverage of power spectrum for discrete time processes was brought forward and updated.
New examples have also been introduced in Chapters 6 and 7 to better illustrate discrete time processes.
Chapter 8 has been restructured to present the introductory concepts of continuous-time and discrete-time linear systems simultaneously.
The book has a Companion Website (www.mheducation.asia/olc/peebles) that includes a downloadable version of the solutions manual for students and instructors as well as JPEG files of the book's figures for instructors.
Table of Contents Chapter 1: Probability
Chapter 2: The Random Variable
Chapter 3: Operations on one Random Variable--Expectation
Chapter 4: Multiple Random Variables
Chapter 5: Operations of Multiple Random Variables
Chapter 6: Random Processes-Temporal Characteristics
Chapter 7: Random Processes-Spectral Characteristics
Chapter 8: Linear Systems with Random Inputs
Chapter 9: Optimum Linear Systems
Chapter 10: Some Practical Applications of the Theory
Appendix A: Review of the Impulse Function
Appendix B: Gaussian Distribution Function
Appendix C: Useful Mathematical Quantities
Appendix D: Review of Fourier Transforms
Appendix E: Table of Useful Fourier Transforms
Appendix F: Some Probability Densities and Distributions
Appendix G: Some Mathematical Topics of Interest