reality, high-resolution estimation is a problem of great interest, and there is a large engineering literature on methods for achieving it. The book does not review them in detail, but it does consider the problem and some of its implications.
Many of the various available detection tests, both in the statistics literature (see Reference [1] for a review) and in the engineering literature over the last 20 years, are not considered. Neither (as mentioned in Section 1.3) does the book consider the issue of threshold SNR, although this is an area in which several researchers (including Prof Quinn) have derived useful results. The book does not attempt to review frequency estimation methods; some which have been the focus of signif-icant research e!ort are mentioned only in passing, or not at all. Similarly, in the area of frequency tracking, the book does not attempt a compre-hensive review; the Kalman "lter and extended Kalman "lter get only a brief mention.
It is di$cult for any book to be up to date, and in some important ways this one is not. For example, a rigorous analysis of MUSIC is present-ed, but a lot has happened since 1990 when a stat-istical analysis of MUSIC was "rst published. Many other subspace methods (for example, ESPRIT) have been proposed as improvements and, in their turn, analysed in the research literature. The burgeoning "eld of Bayesian signal process-ing is not mentioned either. Bayesian approaches to both frequency estimation and tracking (for example particle "ltering) are already important for researchers and will doubtless become so for practitioners soon. This is an understandable omission, since this "eld has grown so rapidly in recent years.
THE BOOK'S STYLE AND VALUE The text is clearly written, and even where the book does not cover issues in detail,
Prof Quinn's own knowledge of the broader "eld leads to clear explanations of the context. I did, though, "nd it slightly frustrating that neither the chapters nor the book had overviews or summaries. The book does what it sets out to do, and by restricting its scope, is able to focus in-depth on speci"c aspects of the problem. This obviously makes it less useful as an overview or reference book, but it leads to a clear #ow of ideas. Due to the very signi"cant limitations of its coverage, it is hard to imagine it being used as a text for engineer-ing courses. The general publisher's preface says that their series aims at &high-quality upper-division textbooks and expository monographs covering all aspects of stochastic applicable mathematics'. This book ful"ls a role I think primarily as a high-quality expository monograph. It could also have a role as a reference for aspecialist option on frequency estimation in a course in statistics and time-series analysis, for example.
It is a nicely presented exposition of one strand of the frequency estimation story, and it is pleasing to see a book devoted to this subject.
MALCOLMD MACLEOD Director of Research, Engineering Department Cambridge ;niversity ¹rumpington Street, Cambridge, CB2 1PZ, ;.K.
REFERENCES
1. Percival DB, Walden AT. Spectral Analysis for
Phys-ical Applications. Cambridge University Press:
Cam-bridge, 1993.
2. Kay SM. Modern Spectral Estimation. Prentice-Hall: Englewood Cli!s, NJ, 1988.
3. Marple SL. Digital Spectral Analysis with Applications. Prentice-Hall: Englewood Cli!s, NJ, 1987.
4. Whalen AD. Detection of Signals in Noise. Academic Press: San Diego, CA, 1971.
Theory of Modelling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems: Second Edition by B. P. Zeigler, H. Praehofer, T. G. Kim, Academic Press, San Diego, CA, 2000.
The "rst edition of this book appeared in 1976 and had only one main author, Bernard P. Zeigler, who discretely edited other appreciated classic text books. The "rst edition was already a &must' read
for the simulation community, which was asking for an updating. The new edition is not just a re-edition with small corrections. The advances in simulation and modelling techniques helped to design a really new edition, necessary to meet the need for a theor-etical foundation. Bernie Zeigler developed a unifying formalism DEVS (Discrete Event System Speci"cation). With DEVS it is not only possible to specify discrete event systems; it is also particularly suited to integrate both continuous
BOOK REVIEWS
91
and discrete paradigms for modelling and simula-tion (discrete time and di!erential equasimula-tions). DEVS features are also present in the systems theory.
The "rst theme of this book is to propose a sound methodology for the construction of complex system models based on the unifying concept of the DEVS Bus. This concept enables the mapping into DEVS of di!erent models expressed in various formalisms such as Petri nets, Hierarchi-cal block diagrams, cellular automata, etc. The second theme focuses on parallel and distributed simulation of discrete event models. Distributed simulation has the potential to support the co-existence of multiple formalisms in multimodels.
In this review I will avoid giving a description of the chapters (19!) and despite the previous praise for the authors, I will try to depict the merits and demerits in comparison with other current and past books. First of all, being in the simulation "eld for 10 years now, I have to cite some complementary references. Without giving an ex-haustive list of all recent valuable books in the simulation "eld, we can "nd other high-quality simulation text books; for instance for continuous simulation [1], for general purpose simulation [2] or even for more speci"c object-oriented simula-tions [3]. However, I must admit that this &Theory of Modelling and Simulation' is the only book available to help construct e$cient object-oriented simulations of DEVS models on parallel and dis-tributed environments. In addition, modellers who have to deal with (HLA) high level architecture compliant simulations will "nd in the book the reference to design integrative simulations.
The most signi"cant features of this book are E The presentation of a comprehensive framework
for continuous and discrete event modelling and simulation.
E The exploration of the mathematical foundation of simulation modelling.
E The discussion of system morphisms for model abstraction and simpli"cation.
E The presentation of a new approach to discrete event simulation of continuous processes.
E The discussion of model credibility and inter-operation.
E The highlighting of design concepts such as modular and hierarchical model composition. E The presentation of a sound methodology to
achieve parallel and distributed simulation models. The reviewer only regrets the lack of public availability for DEVS platforms, despite the quo-tation of a web site, simulation environments (such as DEVSJAVA) are a real need to fully understand practical and theoretical aspects.
This book has multiple facets. From my teach-ing and scienti"c experience, I would say that the primary audience comprises engineers, scientists and other technical people working in academic institutions, but there are many chapters particularly well suited for students at a graduate or even undergraduate level. In my opinion, this was not the case of a previous book from the main author [4] which was an excellent reference for specialists. I am now impressed by this ability to communicate at various levels. I strongly recom-mend this book for the reader interested in any kind of simulation and modelling, its impact on research in control will surely be recognized.
DAVIDR. C. HILL ISIMA Computer Science & Modeling Institute Campus des Cezeaux, BP 10125 A;BIERE Cedex, France E-mail: benny@isima.fr
REFERENCES
1. Cellier FE. Continuous System Modeling. Springer: Berlin, 1991.
2. Fishwick PA. Simulation Model Design: Building
Digital =orlds. Prentice-Hall: Englewood Cli!s, NJ,
1995.
3. Hill D. Object-Oriented Analysis and Simulation. Addison-Wesley: Reading, MA, Longmann: New York, 1996.
4. Zeigler BP. O-O Simulation with Hierarchical Modular
Models: Intelligent Agents and Endomorphic Systems.
Academic Press: London, 1990.
