Home / Back to disciplines / Request exam/desk copy / Purchase / View cart / Checkout
|
Home / Back to disciplines / Request exam/desk copy / Purchase / View cart / Checkout
|
 Introduction to Stochastic Processes
Paul G. Hoel, Sidney C. Port, and Charles J. Stone
An excellent introduction for computer
scientists and electrical and electronics engineers who would like to have a
good, basic understanding of stochastic processes! This clearly written book
responds to the increasing interest in the study of systems that vary in time in
a random manner. It presents an introductory account of some of the important
topics in the theory of the mathematical models of such systems. The selected
topics are conceptually interesting and have fruitful application in various
branches of science and technology. $34.95 list, 203 pages 10-digit ISBN: 0-88133-267-4 13-digit ISBN: 978-0-88133-267-4 © 1972 Table of Contents
1. Markov Chains Markov chains having two states Transition function and initial distribution Examples Computations with transition functions Transient and recurrent states Decomposition of the state space Birth and death chains Branching and queuing chains Proof of results for the branching and queuing chains 2. Stationary Distributions of a Markov Chain Elementary properties of stationary distributions Examples Average number of visits to a recurrent state Null recurrent and positive recurrent states Existence and uniqueness of stationary disruptions Queuing chain Convergence to the stationary disruption Proof of convergence 3. Markov Pure Jump Processes Construction of jump processes Birth and death processes Properties of a Markov pure jump process 4. Second Order Processes Mean and covariance functions Gaussian processes The Wiener process 5. Continuity, Integration, and Differentiation of Second Order Processes Continuity assumptions Integration Differentiation White noise 6. Stochastic Differential Equations, Estimation Theory, and Spectral Distributions First order differential equations Differential equations of order n Estimation theory Spectral distribution
|