This book offers an interesting, straightforward introduction to probability and random processes. While helping readers to develop their problem-solving skills, the book enables them to understand how to make the transition from real problems to probability models for those problems. To keep users motivated, the author uses a number of practical applications from various areas of electrical and computer engineering that demonstrate the relevance of probability theory to engineering practice. Discrete-time random processes are used to bridge the transition between random variables and continuous-time random processes. Additional material has been added to the second edition to provide a more substantial introduction to random processes.

The book's first five chapters form the basis of a traditional, introduction to probability and random variables. In addition to the standard topics, it offers optional sections on modeling, computer methods, combinatories, reliability, and entropy. Chapters 4 through 9 can accommodate a one-semester senior/first-year graduate course on random processes and linear systems, as well as Markov chains and queuing theory. Additional coverage includes cyclostationary random processes, Fourier series and Karhunen-Loeve expansion, continuity, derivatives and integrals, amplitude modulation. Wiener and Kalman filters, and time reversed Markov chains.

Features

Chapter overviews: brief introduction outlining chapter coverage and learning objectives.
Chapter summaries: concise, easy-reference sections providing quick overviews of each chapter's major topics.
Checklist of important terms.
Annotated references: suggestions of timely resources for additional coverage of critical material.
Numerous examples: a wide selection of fully worked-out real-world examples.
Problems: over 700 in all.

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

Description de la librairie

collection of few very good books

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