Intuitive Probability and Random Processes using MATLAB

Steven M. Kay

650 pages, parution le 09/01/2006

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Résumé

Intuitive Probability and Random Processes using MATLAB is an introduction to probability and random processes that merges theory with practice. Based on the author's belief that only "hands-on" experience with the material can promote intuitive understanding, the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have to study this?" Other salient features are:

heavy reliance on computer simulation for illustration and student exercises
the incorporation of MATLAB programs and code segments
discussion of discrete random variables followed by continuous random variables to minimize confusion
summary sections at the beginning of each chapter
in-line equation explanations
warnings on common errors and pitfalls
over 750 problems designed to help the reader assimilate and extend the concepts

Intuitive Probability and Random Processes using MATLAB is intended for undergraduate and first-year graduate students in engineering. The practicing engineer as well as others having the appropriate mathematical background will also benefit from this book.

L'auteur - Steven M. Kay

Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts..." from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.

Sommaire

Computer Simulation
Basic Probability
Conditional Probability
Discrete Random Variables
Expected Values for Discrete Random Variables
Multiple Discrete Random Variables
Conditional Probability Mass Functions
Discrete N-dimensional Random Variables
Continuous Random Variables
Expected Values for Continuous Random Variables
Multiple Continuous Random Variables
Conditional Probability Density Functions
Continuous N-dimensional Random Variables
Probability and Moment Approximations Using Limit Theorems
Basic Random Processes
Wide Sense Stationary Random Processes
Linear Systems and Wide Sense Stationary Random Processes
Multiple Wide Sense Stationary Random Processes
Gaussian Random Processes
Poisson Random Processes
Markov Chains
Appendix A: Glossary of Symbols and Abbreviations
Appendix B: Assorted Math Facts and Formulas
Appendix C: Linear and Matrix Algebra
Appendix D: Summary of Signals, Linear Transforms, and Linear Systems
Appendix E: Answers to Selected Problems

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Steven M. Kay
Parution	09/01/2006
Nb. de pages	650
Format	18,5 x 26,5
Couverture	Relié
Poids	1600g
Intérieur	Noir et Blanc
EAN13	9780387241579
ISBN13	978-0-387-24157-9