Modeling, Analysis, Design and Control of Stochastic Systems

V.G. Kulkarini - Collection Springer Series In Statistics

388 pages, parution le 01/05/1999

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Résumé

An introductory level text on stochastic modelling, suited for undergraduates or graduates in actuarial science, business management, computer science, engineering, operations research, public policy, statistics, and mathematics. It employs a large number of examples to show how to build stochastic models of physical systems, analyse these models to predict their performance, and use the analysis to design and control them. The book provides a self-contained review of the relevant topics in probability theory: In discrete and continuous time Markov models it covers the transient and long term behaviour, cost models, and first passage times; under generalised Markov models, it covers renewal processes, cumulative processes and semi-Markov processes. All the material is illustrated with many examples, and the book emphasises numerical answers to the problems. A software package called MAXIM, which runs on MATLAB, is available for downloading.

Written for: Undergraduate and graduate students

Sommaire

Probability
Univariate Random Variables
Multivariate Random Variables
Conditional Probability and Expectations
Discrete Time Markov Models
Continuous Time Markov Models
Generalized Markov Models
Queuing Models
Optimal Design
Optimal Control

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	V.G. Kulkarini
Collection	Springer Series In Statistics
Parution	01/05/1999
Nb. de pages	388
Format	16,5 x 24
Couverture	Relié
Poids	700g
Intérieur	Noir et Blanc
EAN13	9780387987255
ISBN13	978-0-387-98725-5