Miller and Childers have focused on creating a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course. It is aimed at graduate students as well as practicing engineers, and includes unique chapters on narrowband random processes and simulation techniques. The appendices provide a refresher in such areas as linear algebra, set theory, random variables, and more. Probability and Random Processes also includes applications in digital communications, information theory, coding theory, image processing, speech analysis, synthesis and recognition, and other fields. * Exceptional exposition and numerous worked out problems make the book extremely readable and accessible * The authors connect the applications discussed in class to the textbook * The new edition contains more real world signal processing and communications applications * Includes an entire chapter devoted to simulation techniques
( a ) f ( x ) = C { x ( 1 – x ) } " 3 , 0 < x < 1 , the density function of the ' arc sine law ' . ... Let X be a positive random variable with density function f and distribution function F. Define the hazard function H ( x ) = -log ...
... Probability, Random Processes, and Ergodic Properties, SpringerVerlag, New York, 1987. R. M. Gray, Entropyand Information, SpringerVerlag, New York, 1990. R. M. GrayandL. D.Davisson, An Introduction to Statistical Signal Processing ...
A one-year course in probability theory and the theory of random processes, taught at Princeton University to undergraduate and graduate students, forms the core of this book.
This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics.
The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, ...
The core of this book is a one-year course in probability theory and the theory of random processes, taught at Princeton University.
A comprehensive textbook for undergraduate courses in introductory probability.
With a simple, clear-cut style of writing, the intuitive explanations, insightful examples, and practical applications are the hallmarks of this book. The text consists of twelve chapters divided into four parts.
This book has been written for several reasons, not all of which are academic.
[298] G. Shafer. The Art of Causal Conjecture (MIT Press, 1996). (Cited on p. 477.) [299] G. Shafer and V. Vovk. Probability and Finance: It's Only a Game! (John Wiley & Sons, 2001). (Cited on pp. xxviii, 14, 268, 304, 308.) ...