Modeling, Analysis, Design, and Control of Stochastic Systems

V. G. Kulkarni (Autor)

Buch | Softcover

375 Seiten

2012 | 1999 ed.
Springer-Verlag New York Inc.
978-1-4419-3154-2 (ISBN)

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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.

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.

Erscheint lt. Verlag	10.2.2012
Reihe/Serie	Springer Texts in Statistics
Zusatzinfo	XIV, 375 p.
Verlagsort	New York, NY
Sprache	englisch
Maße	178 x 254 mm
Gewicht	591 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Technik
	Wirtschaft ► Betriebswirtschaft / Management
Schlagworte	Communication • linear optimization • Markov • Markov model • Markov process • MATLAB • Modelling • Operations Research • Probability Theory • programming • Random Variable • Sage • stochastic model • Stochastic Modelling • stochastic models
ISBN-10	1-4419-3154-6 / 1441931546
ISBN-13	978-1-4419-3154-2 / 9781441931542
Zustand	Neuware