Introduction to Stochastic Processes / Edition 1

Introduction to Stochastic Processes / Edition 1

by Erhan Cinlar
     
 

ISBN-10: 0134980891

ISBN-13: 9780134980898

Pub. Date: 01/23/1997

Publisher: Prentice-Hall, Incorporated


This clear presentation of the most fundamental models of random phenomena employs methods that recognize computer-related aspects of theory. The text emphasizes the modern viewpoint, in which the primary concern is the behavior of sample paths. By employing matrix algebra and recursive methods, rather than transform methods, it provides techniques readily

Overview


This clear presentation of the most fundamental models of random phenomena employs methods that recognize computer-related aspects of theory. The text emphasizes the modern viewpoint, in which the primary concern is the behavior of sample paths. By employing matrix algebra and recursive methods, rather than transform methods, it provides techniques readily adaptable to computing with machines.
Topics include probability spaces and random variables, expectations and independence, Bernoulli processes and sums of independent random variables, Poisson processes, Markov chains and processes, and renewal theory. Assuming some background in calculus but none in measure theory, the complete, detailed, and well-written treatment is suitable for engineering students in applied mathematics and operations research courses as well as those in a wide variety of other scientific fields. Many numerical examples, worked out in detail, appear throughout the text, in addition to numerous end-of-chapter exercises and answers to selected exercises.

Product Details

ISBN-13:
9780134980898
Publisher:
Prentice-Hall, Incorporated
Publication date:
01/23/1997
Pages:
402
Product dimensions:
6.22(w) x 8.92(h) x 0.88(d)

Related Subjects

Table of Contents


Preface
1. Probability Spaces and Random Variables
2. Expectations and Independence
3. Bernoulli Processes and Sums of Independent Random Variables
4. Poisson Processes
5. Markov Chains
6. Limiting Behavior and Applications of Markov Chains
7. Potentials, Excessive Functions, and Optimal Stopping of Markov Chains
8. Markov Processes
9. Renewal Theory
10. Markov Renewal Theory
Afterword
Appendix. Non-Negative Matrices
References
Answers to Selected Exercises
Index of Notations
Subject Index 

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >