Modeling, Analysis, Design, and Control of Stochastic Systems (Springer Texts in Statistics) | 
 enlarge | Author: Vidyadhar G. Kulkarni
Publisher: Springer
Category: Book
List Price: $104.00
Buy New: $32.65
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Rating:  2 reviews
Sales Rank: 1273772
Media: Hardcover
Pages: 374
Number Of Items: 1
Shipping Weight (lbs): 1.6
Dimensions (in): 9.6 x 7.3 x 1
ISBN: 0387987258
Dewey Decimal Number: 519.23
EAN: 9780387987255
Publication Date: December 15, 2000
Availability: Usually ships in 1-2 business days
Condition: THIS ITEM IS UNUSED AND IN GOOD CONDITION. IT MAY HAVE SLIGHT SHELFWEAR BUT OTHERWISE IT IS FINE.
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Product Description
This is an introductory level text on stochastic modeling. It is suited for undergraduate or graduate students in actuarial science, business management, computer science, engineering, operations research, public policy, statistics, and mathematics. It employs a large number of examples to teach how to build stochastic models of physical systems, analyze 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. The rest of the book is devoted to important classes of stochastic models. In discrete and continuous time Markov models it covers the transient and long term behavior, cost models, and first passage times. Under generalized Markov models, it covers renewal processes, cumulative processes and semi-Markov processes. All the material is illustrated with many examples. There is a separate chapter on queueing models. In the chapter on design the author shows how the techniques developed in the text can be used to optimize the performance of a system. Finally, in the last chapter, linear programming is used to compute optimal control policies for stochastic systems. The book emphasizes numerical answers to the problems. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Craolina at Chapel Hill. He has authored a graduate level text 'Modeling and Analysis of Stochastic Systems' and research articles on stochastic models of queues, computer systems and telecommunication systems. He holds a patent on traffic management in telecommunication networks, and he has served as an editor and associate editor of Stochastic Models and Operations Research Letters.
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| Customer Reviews:
 intuitive but formal text for undergrad (maybe for grad too) November 6, 2004
Luz Adriana (Michigan, USA)
This is a very good text to study stochastic processes for the first time. It contains a review on basic probability material in the four first chapters, which is quite extensive for a review, but very useful, since usually undergraduate students have covered in detail only parts of the material they will need to study Markov Chains and other stochastic processes.
Grad students will find probably find it useful too, since after the review, discrete and continuous Markov chains, queuing models and other topics are presented and illustrated with many examples. They serve to clarify propositions and theorems that are formally proved.
In general, I think this book helps to develop the intuition necessary to use Markov processes in many practical applications, and understand higher level texts.
Of course, having a broad topic coverage at introductory level, some more advenced topics (like positive and null recurrency) had to be left out, so grad students will need some other reference too (Kulkarni has a grad text, in case you like this one).
 Book that needs improvement January 2, 2005
C. Waldorf (Seattle, WA)
1 out of 1 found this review helpful
This is probably ideal as a reference source for a graduate student or professor who knows stochastics very well already.
However, if you are a novice trying to learn about stochastics and want good explanations and examples with an appropriate buildup, I would not recommend the book.
As an example, the review discussion of probability in the first four chapters didn't even come close to comparing with the probability book I used in another class. If you are near a bookstore, you can easily verify this. I imagine that this comparison (or lack thereof) would hold for many other probability textbooks. Also, if presentation makes a difference to you, this is quite minimalist.
Another area that I found lacking is that the answers in the back just provide a numerical answer without any explanation to how solutions were arrived at. While this is often the case for other books, the author did not provide a sufficient base for a novice to work the problems. As a result, most of the end of chapter problems were of little use in helping me better learn the materials. A good workbook or better explanations would be very helpful.
While there are certainly couple areas that I found worthwhile and this does appear to be one of the only books on this niche area (the lack of competition may explain a lot of why the shortcomings exist and why this doesn't have the feel of real textbook), this first edition book needs some serious work to make it truly effective and user friendly.
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