Probability and Stochastic Processes : Friendly Introduction for Electrical and Computer Engineers - Yates, Roy D.

Probability and Stochastic Processes : Friendly Introduction for Electrical and Computer Engineers

Roy D. Yates

Yayınevi: John Wiley High Education

Yayın tarihi: 07/1998

ISBN: 9780471178378

Yazar : David J. Goodman

Ciltli | İngilizce | 480 Sayfa | Büyük boy  | 

Tür: Matematik-İstatistik  |  Genel Mühendislik

What Does Winning the Lottery Have To do with Engineering? Whether you're trying to win millions in the lottery or designing a complex computer network, you're applying probability theory. Although you encounter probability applications everywhere, the theory can be deceptively difficult to learn and apply correctly. This text will help you grasp the concepts of probability and stochastic processes and apply them throughout your careers. These concepts are clearly presented throughout the book as a sequence of building blocks that are clearly identified as either an axiom, definition, or theorem. This approach provides you with a better understanding of the material which you'll be able to use to solve practical problems. Key Features:

* The text follows a single model that begins with an experiment consisting of a procedure and observations.
* The mathematics of discrete random variables appears separately from the mathematics of continuous random variables
. * Stochastic processes are introduced in Chapter 6, immediately after the presentation of discrete and continuous random variables. Subsequent material, including central limit theorem approximations, laws of large numbers, and statistical inference, then use examples that reinforce stochastic process concepts.
* An abundance of exercises are provided that help students learn how to put the theory to use.

Table of Contents

Experiments, Models, and Probabilities.
Discrete Random Variables.
Multiple Discrete Random Variables.
Continuous Random Variables.
Multiple Continuous Random Variables.
Stochastic Processes.
Sums of Random Variables.
The Sample Mean.
Statistical Inference.
Random Signal Processing.
Renewal Processes and Markov Chains.
Appendices.
References.
Index.

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