Product Description
This Proceedings contains the papers presented at the first IFAC Workshop on Advanced Fuzzy-Neural Control, held at Valencia, Spain, on 15-16 October 2001.This is the first IFAC technical meeting specifically devoted to fuzzy and neural control.

The use of artificial intelligence techniques has been expanded to many engineering areas. Fuzzy systems, neural networks, genetic algorithms and, in general, soft computing techniques are regarded as alternatives for the solution of complex problems involving non-linear systems, optimisation and/or dealing with approximate knowledge. Fuzzy logic controllers are undoubtedly one of the most successful applications of fuzzy logic theory.

The issues covered in the Proceedings include:

Stability, robustness and adaptation

Learning and local models

Structures

Design methodologies

Heuristics vs. model based design

Applications in process control

Applications in robotics

In addition to the papers, this Proceedings includes a novel section which summarises ideas and conclusions on fuzzy logic controllers from the experts attending the IFAC Workshop.

... Read more

Product Description
We eavesdrop on a game of checkers where a convoluted jumping sequence has been set up and the action is about to begin..... We let the first player make his move; his jumps - and therefore acquires a bunch of his opponent's checkers. We let the second player make his retaliatory move; he jumps - and therefore acquires a bunch of his opponent's checkers. They each savor the results for a moment, then one of them puts the situation into words: "I love this game because everybody wins. You took more checkers than me and I took more checkers than you..." In checkers, we can see the stupidity; in economics we cannot. But all that must change if we expect any semblance of a reasonably non-violent future. The basic problem is that we don't make money, we acquire money and, regardless of any obfuscating detours though our intertwined businesses and/or our multifariuos levels of government - we acquire it only from each other. Read this book. But let there be absolutely no misunderstanding, it is bitter bitter medicine. You won't like what you read; you won't believe what you read; but your children need you to read it. ... Read more

Product Description
Fuzzy logic enables people preparing environmental impact statements to quantify complex environmental, economic and social conditions.  This reduces the time and cost of assessments, while producing justifiable results.  ... Read more

Product Description
A number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. This volume explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas. "Genetic Fuzzy Systems" represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective.It aims to provide a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms - specifically for probabilists, analysts, statisticians and mathematicians. ... Read more

Customer Reviews (3)

A Complete Book
It's a great book! Introduce the presentation covering the basic topics in Genetic Algorithm and Fuzzy Logic. The methodologies of the Genetic Fuzzy Systems are presented in a very clear way.

A major source on genetic fuzzy systems
The volume brings an outstanding presentation of the major issues, ideas, concepts and algorithms to design and develop fuzzy systems using gentic algorithms. A field of major relevance for researchers and practioners, genetic fuzzy systems provides a major methodological substract of significant impact in practice. The book is unique in its contents and presentation. Chapters begin with the key concepts and smoothly grows to advanced concepts in a clear and very understandable and motivating way. The material mirrors the state of the art in the area of genetic fuzzy systems and contains the most recent results available until its publication. Written by renowned, internationally recognized researchers, the book is mandatory to all who are interested in the field of computational intelligence, its foundations and applications.

Summary of contents by the author
In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy
systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn
the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy
systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning
processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as
genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas. Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from
a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in
the domain of fuzzy systems and genetic algorithms. ... Read more

Product Description

This book constitutes the refereed proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2009, held in Delhi, India in December 2009 in conjunction with the Third International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009. RSFDGrC 2009 is the core component of a broader Rough Set Year in India initiative, RSIndia09.

The 56 revised full papers presented together with 6 invited papers and a report on the Rough Set Year in India 2009 project were carefully reviewed and selected from a total of 130 submissions. The papers are organized in topical sections on foundations of rough sets and beyond; rought set algorithms and applications; fuzzy set foundations and applications; data mining and knowledge discovery; clustering and current trends in computing; and information retrieval and text mining.

Product Description
Probabilists and fuzzy enthusiasts tend to disagree about which philosophy is best and they rarely work together. As a result, textbooks usually suggest only one of these methods for problem solving, but not both. This book, with contributions from 15 experts in probability and fuzzy logic, is an exception. The contributing authors, investigators from both fields, have combined their talents to provide a practical guide showing that both fuzzy logic and probability have their place in the world of problem solving. They work together with mutual benefit for both disciplines, providing scientists and engineers with examples of and insight into the best tool for solving problems involving uncertainty.

Fuzzy Logic and Probability Applications: Bridging the Gap makes an honest effort to show both the shortcomings and benefits of each technique, and even demonstrates useful combinations of the two. It provides clear descriptions of both fuzzy logic and probability, as well as the theoretical background, examples, and applications from both fields, making it a useful hands-on workbook for members of both camps. It contains enough theory and references to fundamental work to provide firm ground for both engineers and scientists at the undergraduate level and above. Readers should have a familiarity with mathematics through calculus.

Use of this book is not restricted to a specific course or application. It can be used in teaching probability, fuzzy logic, general problem solving, or in any course in which probability and fuzzy logic are not normally taught together. It has applications in control theory and artificial intelligence, knowledge acquisition/management, and risk/reliability analysis.

Contents
Foreword by Lotfi A. Zadeh; Foreword by Patrick Suppes; Preface; Part I: Fundamentals; Chapter 1: Introduction; Chapter 2: Fuzzy Set Theory, Fuzzy Logic, and Fuzzy Systems; Chapter 3: Probability Theory; Chapter 4: Bayesian Methods; Chapter 5: Considerations for Using Fuzzy Set Theory and Probability Theory; Chapter 6: Guidelines for Eliciting Expert Judgment as Probabilities or Fuzzy Logic; Part II: Applications; Chapter 7: Image Enhancement: Probability Versus Fuzzy Expert Systems; Chapter 8: Engineering Process Control; Chapter 9: Structural Safety Analysis: A Combined Fuzzy and Probability Approach; Chapter 10: Aircraft Integrity and Reliability; Chapter 11: Auto Reliability Project; Chapter 12: Control Charts for Statistical Process Control; Chapter 13: Fault Tree Logic Models; Chapter 14: Uncertainty Distributions Using Fuzzy Logic; Chapter 15: Signal Validation Using Bayesian Belief Networks and Fuzzy Logic; Index. ... Read more

Product Description
This book examines fuzzy relational calculus theory with applications in various engineering subjects. The scope of the text covers unified and exact methods with algorithms for direct and inverse problem resolution in fuzzy relational calculus. Extensive engineering applications of fuzzy relation compositions and fuzzy linear systems (linear, relational and intuitionistic) are discussed. Some examples of such applications include solutions of equivalence, reduction and minimization problems in fuzzy machines, pattern recognition in fuzzy languages, optimization and inference engines in textile and chemical engineering, etc. A comprehensive overview of the authors' original work in fuzzy relational calculus is also provided in each chapter. The attached CD-Rom contains a toolbox with many functions for fuzzy calculations, together with an original algorithm for inverse problem resolution in MATLAB. This book is also suitable for use as a textbook in related courses at advanced undergraduate and graduate levels. ... Read more

Product Description
Provides a timely and important introduction to fuzzy cluster analysis, its methods and areas of application, systematically describing different fuzzy clustering techniques so the user may choose methods appropriate for his problem. It provides a very thorough overview of the subject and covers classification, image recognition, data analysis and rule generation. The application examples are highly relevant and illustrative, and the use of the techniques are justified and well thought-out.

Features include:

* Sections on inducing fuzzy if-then rules by fuzzy clustering and non-alternating optimization fuzzy clustering algorithms

* Discussion of solid fuzzy clustering techniques like the fuzzy c-means, the Gustafson-Kessel and the Gath-and-Geva algorithm for classification problems

* Focus on linear and shell clustering techniques used for detecting contours in image analysis

* Accompanying software and data sets pertaining to the examples presented, enabling the reader to learn through experimentation

* Examination of the difficulties involved in evaluating the results of fuzzy cluster analysis and of determining the number of clusters with analysis of global and local validity measures

This is one of the most comprehensive books on fuzzy clustering and will be welcomed by computer scientists, engineers and mathematicians in industry and research who are concerned with different methods, data analysis, pattern recognition or image processing. It will also give graduate students in computer science, mathematics or statistics a valuable overview. ... Read more

Customer Reviews (3)

Excellent advanced book in fuzzy cluster analysis
Previous reviews are correct, this is not a book for beginners. This is an advanced text for specialists in the area of fuzzy clustering, and as such it is an excellent work. Standard fuzzy c-means, Gustafson-Kessel c-means and Gath-Geva c-means are drawn together in a single modeling framework for near-arbitrary cluster shapes. The cluster validity problem is examined in depth, and experimental results in image analysis are used to illustrate the theoretical material. An excellent monograph.

Worst book I have ever read
This book is ridiculous. It has too many unnecessary and, even worse, unclear definitions. It never gives us the meanings of the strange symbols in those absurd definitions. If you want to understand fuzzy cluster analysis in a relatively short time and do not want to suffer, please do not buy this book.

Too many unnecessary definitions
This is not a good book for people who want to understand the basic idea of fuzzy cluster analysis in a short time. ... Read more

Product Description
This book presents in a systematic and comprehensive manner the modeling of uncertainty, vagueness, or imprecision, alias "fuzziness," in just about any field of science and engineering. It delivers a usable methodology for modeling in the absence of real-time feedback.The book includes a short introduction to fuzzy logic containing basic definitions of fuzzy set theory and fuzzy rule systems. It describes methods for the assessment of rule systems, systems with discrete response sets, for modeling time series, for exact physical systems, examines verification and redundancy issues, and investigates rule response functions.Definitions and propositions, some of which have not been published elsewhere, are provided; numerous examples as well as references to more elaborate case studies are also given.Fuzzy rule-based modeling has the potential to revolutionize fields such as hydrology because it can handle uncertainty in modeling problems too complex to be approached by a stochastic analysis. There is also excellent potential for handling large-scale systems such as regionalization or highly non-linear problems such as unsaturated groundwater pollution. ... Read more

Customer Reviews (1)

Excellent intro to fuzzy rule-based modeling, with examples.
Many good books have recently been published on fuzzy rule-based systems for control, but few authors have dealt with open systems. The book by Bardossy and Duckstein, which does an excellent job of introducing fuzzy rule-based modeling of open systems, may stimulate more research in this area. Indeed, the realistic examples presented in the book are very convincing. More emphasis could however have been put on the complex processes of selecting input variables and defining fuzzy rules. The discussion, in the introduction, of the differences between fuzzy numbers and probability distributions is certainly too short to convince a statistician of the usefulness of fuzzy sets for uncertainty modeling. However, if the book does not contribute to this philosophical debate, it certainly does a good job of showing the practical value of fuzzy models for nonparametric modeling of open systems. ... Read more

Product Description
Fuzzy logic provides a unique method of approximate reasoningin an imperfect world. This text is a bridge to the principles offuzzy logic through an application-focused approach to selected topicsin Engineering and Management. The many examples point to the richersolutions obtained through fuzzy logic and to the possibilities ofmuch wider applications. There are relatively few texts available at present in fuzzy logicapplications. The style and content of this text is complementary tothose already available. New areas of application are presented in agraded approach in which the underlying concepts are first described.The text is broadly divided into two parts which treat Processes andMaterials and also System Applications. The level enables a selection of the text to be made for the substanceof a senior undergraduate level course. There is also sufficientvolume and quality for the basis of a postgraduate course. A morerestricted and judicious selection can provide the material for aprofessional short course. ... Read more

Product Description
Dieses bewährte Lehrbuch ist aus einem Vorlesungszyklus für Studiengänge der Ingenieur- und Wirtschaftswissenschaften sowie der Informatik heraus entstanden. Es schlägt eine Brücke zwischen der rein theoretischen Darstellung und der angwandten Mathematik; es zeichnet sich durch gute Lesbarkeit sowie leichte Verständlichkeit aus. Vollständig durchgerechnete Beispiele ergänzen das didaktische Konzept.
Damit eignet sich das Werk nicht nur zum Gebrauch neben Vorlesungen an Hochschulen und Fachhochschulen, sondern auch zum Selbststudium, insbesondere für Studienanfänger.
Nach einer kurzen Lieferlücke macht dieser Nachdruck das erfolgreiche Buch wieder verfügbar. ... Read more

Product Description
This monograph is intended for a graduate course ofengineering and management science, as well as for personswho want an introductory and a capsule look into thetheories and methodologies of multiple attributedecisionmaking under a fuzzy environment. Moving from classicalMADMintroduces a great deal of complexity to the decisionanalysis. In a fuzzy environment, the decision analysis isextended to not only consider the aggregation of performancescores (which are fuzzy) but also thecomparison of fuzzynumbers which cannot be easily compared as in the caseofreal numbers. Chapter II gives an overview of the classicalMADM.Chapter III presents the basic concepts and themathematical operations offuzzy set theory with figures andsimple numerical examples in aeasy-to-read andeasy-to-follow manner. Chapter IV deals with the fuzzyranking methods. Fuzzy ranking methods are widely used inmanyaspects of fuzzy applications (especially fuzzyoptimization procedure). Asystematic classification ofnearly two dozens of existing ranking methodsis presented.In chapter IV, a system for classifying over one dozenfuzzyMADM methods is presented. The concept, algorithm, andthecharacteristics of each method are discussed. Thecomputational procedure of each method is illustrated bysolving a simple numerical example. ... Read more

Product Description
Contains the Proceedings of the International Summer School on Fuzzy Logic held in June 16-20, 1998, at the University of Ferrara, Italy. ... Read more

Product Description
Webster's bibliographic and event-based timelines are comprehensive in scope, covering virtually all topics, geographic locations and people. They do so from a linguistic point of view, and in the case of this book, the focus is on "Fuzzy," including when used in literature (e.g. all authors that might have Fuzzy in their name). As such, this book represents the largest compilation of timeline events associated with Fuzzy when it is used in proper noun form. Webster's timelines cover bibliographic citations, patented inventions, as well as non-conventional and alternative meanings which capture ambiguities in usage. These furthermore cover all parts of speech (possessive, institutional usage, geographic usage) and contexts, including pop culture, the arts, social sciences (linguistics, history, geography, economics, sociology, political science), business, computer science, literature, law, medicine, psychology, mathematics, chemistry, physics, biology and other physical sciences. This "data dump" results in a comprehensive set of entries for a bibliographic and/or event-based timeline on the proper name Fuzzy, since editorial decisions to include or exclude events is purely a linguistic process. The resulting entries are used under license or with permission, used under "fair use" conditions, used in agreement with the original authors, or are in the public domain. ... Read more

Product Description
The study of nonlinear dynamical systems has advanced tremendously, making a big impact on science and technology. This is an exploration of all the techniques and methods used in nonlinear dynamics. The concepts and underlying mathematics are discussed in detail, and the numerical and symbolic methods are implemented in C++, SymbolicC++ and Java. Object-oriented techniques are also applied. More than 100 ready-to-run programs are included. The text has also been designed for a one-year course at both the junior and senior levels in nonlinear dynamics. The topics discussed in the book are part of e-learning and distance learning courses conducted by the International School for Scientific Computing. ... Read more

Customer Reviews (5)

Exact same content as the cheaper and sturdy paperback version
Overall, this is a good book on the various subjects it covers, but I have to wonder - why would you buy this expensive hardcover version when the paperback version costs a little more than half what this hardcover costs? The contents are the same, the publication date is the same, and having had my softcover copy for two years and made heavy use of it, it seems to be standing up to the wear and tear just fine.

This book is an overview of all of the components of nonlinear dynamics. Nonlinear dynamics is a field of study that enables well-constructed predictive modeling of systems that might be difficult to solve otherwise. Such continuous systems were first widely modeled by ordinary and differential equations, but with the passage of time there are now tools and mathematical models at our disposal that make for a much more concise model of many systems. This workbook tries to touch on all of those mathematical tools.

The first six chapters of the book has to do with modeling such complex systems in general, and the rest of the book is a survey of the tools needed to perform complex modeling. The book's format is that of briefly explaining a concept in a few pages, and then presenting a computer program that demonstrates the concept just explained. The explanations are very clear and concise, there are plenty of equations shown, and the accompanying code is well commented. If you want to really drill deeply into any of the concepts then you are going to need some other books. I suggest that for further reading for the mathematically inclined that you pick up "Chaos: An Introduction to Dynamical Systems" by Kathleen Alligood. For scientists that want to see specific problems that can be solved by dynamical systems I suggest the excellent "Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering" by Strogatz. The only real complaint I have against this book is that there is uneven coverage of different tools. For example, the author has a great deal to say about neural networks and fuzzy logic, but has very short chapters covering discrete wavelets and cellular automata. More material would have been great, since it is hard to find good books on discrete wavelets and cellular automata in particular. Some readers may also be annoyed that much of the book are code listings of the various demonstration programs.

Overall, I would highly recommend this as one of several books that anyone interested in dynamical systems should definitely own. In particular, those individuals interested in the techniques of algorithmic composition of music might find this book a good jumping off point for studying the tools and techniques that make such compositions possible.

explains many key ideas
Here is a text of advanced nonlinear dynamics. Geared towards the intensive use of computers to perform the necessary grungework. Steeb hits on many important ideas that have emerged in recent decades. He shows the interrelation between chaotic phenomena and fractals, and how fractals can be used to describe the onset to chaos.

The Hidden Markov Models have proved to be the key idea in current Automatic Speech Recognisers. A tribute to the practical nature of this idea.

Steeb's discussion of neural networks and genetic algorithms is enough to get you started in this field. Ideas like forward and back propagation for feedback are clearly explained.

The sample code should be welcomed. It lets you see for yourself on your own computer, and to tinker with the various parameters. Though I am unsure about the choice of code in Symbolic C++. Unlike C++ or Java, this is a rarely used language.

Good overview of nonlinear dynamics
This book is an overview of all of the components of nonlinear dynamics. Nonlinear dynamics is a field of study that enables well-constructed predictive modeling of systems that might be difficult to solve otherwise. Such continuous systems were first widely modeled by ordinary and differential equations, but with the passage of time there are now tools and mathematical models at our disposal that make for a much more concise model of many systems. This workbook tries to touch on all of those mathematical tools. The first six chapters of the book has to do with modeling such complex systems in general, and the rest of the book is a survey of the tools needed to perform complex modeling. The book's format is that of briefly explaining a concept in a few pages, and then presenting a computer program that demonstrates the concept just explained. The explanations are very clear and concise, there are plenty of equations shown, and the accompanying code is well commented.If you want to really drill deeply into any of the concepts then you are going to need some other books. I suggest that for further reading for the mathematically inclined that you pick up "Chaos: An Introduction to Dynamical Systems" by Kathleen Alligood. For scientists that want to see specific problems that can be solved by dynamical systems I suggest the excellent "Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering" by Strogatz. The only real complaint I have against this book is that there is uneven coverage of different tools. For example, the author has a great deal to say about neural networks and fuzzy logic, but has very short chapters covering discrete wavelets and cellular automata. More material would have been great, since it is hard to find good books on discrete wavelets and cellular automata in particular. Some readers may also be annoyed that much of the book are code listings of the various demonstration programs. Overall, I would highly recommend it as one of several books that anyone interested in dynamical systems should definitely own. In particular, those individuals interested in the techniques of algorithmic composition of music might find this book a good jumping off point for studying the tools and techniques that make such compositions possible.

Helpful in some sections
The topics covered in this book are all important from the standpoint of applications in physics, engineering, computer science, financial engineering, and computational biology. It is written for the person just getting started in these topics, and the author does a fairly good job of discussing them. Readers should not expect, and they will not get, in-depth discussions on these topics, as this would swell the book to 10 times the size. They will however get preparation for moving on to more advanced and complete treatments.

Nonlinear and chaotic maps are considered in chapter 1, with elementary definitions given and six different examples of maps discussed. In discussing the calculation of numerical trajectories of maps, the author deals with the problem of large initial values for the maps and how to implement these in SymbolicC++ and Java. He also shows how to write/read data to a file using C, C++, and JAVA. The exception handling capability of JAVA comes out nicely, but no performance comparison between the three languages for simulating the maps is given by the author. The language REDUCE is used to discuss the stability of the fixed points of the logistic equation, but the code would be useless to the reader who did not have REDUCE since some of the function calls are hidden from the reader. Useful programs are given for calculating the Lyapunov and autocorrelation functions. In addition, C++ programs are given for evaluating the correlation integral for the Henon map. The programs he develops in this chapter can serve as a quick benchmark for one's own programs that calculate the same quantities.

In chapter 2, the author discusses methods for studying time series, including the Lyapunov and Hurst exponents. These two quantities are of enormous importance in the study of dynamical systems, financial data, and network performance. The C++ program that the author gives for calculating the Hurst exponent will not work for arbitrary time intervals. This is followed in the next chapter by a consideration of autonomous systems of ordinary differential equations. The classification of fixed points is considered, and the important concept of a homoclinic orbit. The author gives a nice JAVA program that finds the homoclinic orbit of an anharmonic differential equation using the Lie series technique. The phase portrait of the Van der Pol oscillator is calculated using the Runge-Kutta technique in a C++ program, along with the Lotka-Volterra system from mathematical biology.

Hamiltonian mechanics is discussed in chapter 4, with the important Henon-Heiles model from astrophysics is discussed and JAVA programs given for studying its behavior using the Poincare section technique. Newcomers to this technique will appreciate seeing it done here explicitly.Integrability of Hamiltonian systems using the Lax representation and Floquet theory are also treated, but only at a very rudimentary level. Dissipation is included in the next chapter, and the author discusses the classification of fixed points according to their stability. Lyapunov exponents are again brought into the picture, and the phenomenon of hyperchaos is discussed. Some bifurcation theory is introduced with an example of the Hopf bifurcation. Chapter 6 studies nonlinear driven systems, with the Duffing oscillator treated, and the author gives a useful program for calculating the autocorrelation function of this system. The controlling of chaos with feedback and non-feedback controls is the subject of the next chapter, mostly in the context of difference maps. Fractals finally get introduced in chapter 8, with iterated function systems defined but proofs of their properties omitted. The author gives programs for calculating various popular fractals, such as the dragon, Sierpinski gasket, Koch curve, the Mandelbrot set, and the Julia set. The main disappointment in this chapter is that the author does not give programs for calculating the Hausdorff dimension or capacity, quantities that are notoriously difficult to get a meaningful computational handle on.

The author switches gears in the next chapter and discusses cellular automata, which have recently made a comeback, especially in research on quantum computation. The discussion is too brief however, and does not allow the reader to gain an appreciation of the properties of these important objects. Chapter 10 gives a brief overview of some techniques for solving differential equations, such as the Euler method and the Lie series technique. The latter is not commonly treated in beginning books so its inclusion here is helpful. Symplectic integration is also discussed briefly, but the author does not discuss how to check the integrators using backward integration, which is commonly used in conservative systems modeled by symplectic maps.

Chapter 11, covering neural networks, is the most well-written in the book, and the newcomer to the field will get a fairly decent introduction to the subject. The supplied programs serve to illustrate some of the important concepts in neural networks, such as the Hopfield model, the Kohonen network, the perceptron learning algorithm, and the back-propagation algorithm.

Chapter 12 is an introduction to genetic algorithms, and I find this one particularly nice also, as it does give a rudimentary introduction to what evolutionary algorithms are all about, and gives some elementary genetic programs that find the maximum of one- and two-dimensional maps. He also discusses simulated annealing, and gives a useful program that allows the reader to see clearly how this technique works.

The last chapter covers fuzzy sets and fuzzy logic, which has also taken on importance in recent years, especially in data mining and financial engineering. The programs given to illustrate the concepts are particularly interesting from the standpoint of coding in C++, as the author uses friend functions and operating overloading in some of them. The reader gets a good overview of fuzzy reasoning and fuzzy rule-based systems.

Useful information, poor presentation
The information was useful & approprate to the topic.I'd rank it as an average quality refence but a very poor text book.

The text is poorly written.The code is simple and easy to understand, but not very objectoriented.There is not enough explanation of the code.The code is notelectronically available.

The treatment was very mathematical but lackingin explanation & application examples.There were plenty ofdeffinitions, but not enough examples. ... Read more

Product Description
Provides a mathematical framework for clarifying the interconnections between information theory, automatic theorem proving, computer vision, robotics, and artificial intelligence, and for expressing ideas of linear and multilinear algebra, projective and affine geometry, and other areas in science and engineering. Contains an errata for pages 260-261. DLC: Geometry, Algebraic ... Read more

Customer Reviews (1)

I have not read this book, but can provide this information
Part I Advances in Geometric Algebra


Chapter 1
Old Wine in New Bottles: A New Algebraic Framework for Computational Geometry,
David Hestenes
1.1 Introduction
1.2 Minkowski Algebra
1.3 Conformal Split
1.4 Models of Euclidean Space
1.5 Lines and Planes
1.6 Spheres and Hyperplanes
1.7 Conformal and Euclidean Groups
1.8 Screw Mechanics
1.9 Conclusions

Chapter 2
Universal Geometric Algebra
Garret Sobczyk
2.1 Introduction
2.2 The Universal Geometric Algebra
2.3 Matrices of Geometric Numbers
2.4 Linear Transformations
2.5 Pseudo-Euclidean Geometries
2.6 Affine and Projective Geometries
2.7 Conformal Transformations

Chapter 3
Realizations of the Conformal Group
Jose Maria Pozo and Garret Sobczyk
3.1 Introduction
3.2 Projective Geometry
3.3 The Conformal Representant and Stereographic Projection
3.4 Conformal Transformations and Isometries
3.5 Isometries in No
3.6 Compactification
3.7 Mobius Transformations

Chapter 4
Hyperbolic Geometry
Hongbo Li
4.1 Introduction
4.2 Hyperbolic Plane Geometry with Clifford Algebra
4.3 Hyperbolic Conformal Geometry with Clifford Algebra
4.4 A Universal Model for the ConformalGeometries of the Euclidean, Spherica and Double-Hyperbolic Spaces
4.5 Conclusion

Part II Theorem Proving

Chapter 5
Geometric Reasoning With Geometric Algebra
Dongming Wang
5.1 Introduction
5.2 Clifford Algebra for Euclidean Geometry
5.4 Proving Identities in Clifford Algebra

Chapter 6
Automated Theorem Proving
Hongbo Li
6.1 Introduction
6.2 A general Framework for Clifford algebra and Wu's Method
6.3 Automated Theorem Proving in Euclidean Geometry and Other
Classical Geometries
6.4 Automated Theorem Proving in Differential Geometry}{116}
6.5 Conclusion

Part III Computer Vision

Chapter 7
The Geometry Algebra of Computer Vision
Eduardo Bayro Corrochano and Joan Lasenby
7.1 Introduction
7.2 The Geometric Algebras of 3-D and 4-D Spaces
7.3 The Algebra of Incidence
7.4 Algebra in Projective Space
7.5 Visual Geometry of $n$ Uncalibrated Camera
7.6 Conclusions

Chapter 8
Using Geometric Algebra for Optical Motion Capture
Joan Lasenby and Adam Stevenson
8.1 Introduction
8.2 External and Internal Calibration
8.3 Estimating the External Parameters
8.4 Examples and Results
8.5 Extending to Include Internal Calibration
8.6 Conclusions

Chapter 9
Bayesian Inference and Geometric Algebra: An Application to Camera Localization
Chris Doran
9.1 Introduction
9.2 Geometric Algebra in Three Dimensions
9.3 Rotors and Rotations
9.4 Rotor Calculus
9.5 Computer Vision
9.6 Unknown range data
9.7 Extension to three cameras
9.8 Conclusions

Chapter 10
Projective Reconstruction of Shape and Motion Using Invariant Theory
Eduardo Bayro Corrochano and Vladimir Banarer
10.1 Introduction
10.2 3-D Projective Invariants from Multiple Views
10.3 Projective Depth
10.4 Shape and Motion
10.5 Conclusions

Part IV Robotics

Chapter 11
Robot Kinematics and Flags

11.1 Introduction
11.2 The Clifford Algebra
11.3 Flags
11.4 Robots
11.5 Concluding Remarks

Chapter 12
The Clifford Algebra and the Optimization of Robot Design
Shawn G. Ahlers and John Michael McCarthy
12.1 Introduction
12.2 Literature Review
12.3 Overview of the Design Algorithm
12.4 Double Quaternions
12.5 The Task Trajectory
12.6 The Design of the TS Robot
12.7 The Optimum TS Robot
12.8 Conclusion

Chapter 13
Eduardo Bayro Corrochano and Garret Sobczyk
13.1 Introduction
13.2 The General Linear Group
13.3 Algebra of Incidence
13.4 Rigid Motion in the Affine Plane
13.5 Application to Robotics
13.6 Application II:
The design of an image filter
Recognition of hand gestures
The meet filter
13.7 Conclusion

Part V Quantum and Neural Computing, and Wavelets

Chapter 14
Geometric Algebra in Quantum Information Processing
by Nuclear Magnetic Resonance
Timothy F. Havel, David G. Cory, Shyamal S. Somaroo, and Ching-Hua Tseng
14.1 Introduction
14.2 Multiparticle Geometric Algebra
14.3 Algorithms for Quantum Computers
14.4 NMR and the Product Operator Formalism
14.5 Quantum Computing by Liquid-State NMR
14.6 States and Gates by NMR
14.7 Quantum Simulation by NMR
14.8 Remarks on Foundational Issues

Chapter 15
Geometric Feedforward Neural Networks and Support Multivector Machines
Eduardo Bayro Corrochano and Refugio Vallejo

15.1 Introduction
15.2 Real Valued Neural Networks
15.3 Complex MLP and Quaternionic MLP
15.4 Geometric Algebra Neural Networks
15.5 Learning Rule
15.6 Experiments Using Geometric Feedforward Neural Networks
15.7 Support Vector Machines in Geometric Algebra
15.8 Experimental Analysis of Support Multivector Machines
15.9 Conclusions

Chapter 16
Image Analysis Using Quaternion Wavelets
Leonardo Traversoni
16.1 Introduction
16.2 The Static Approach
16.3 Clifford Multiresolution Analyses
16.4 Haar Quaternionic Wavelets
16.5 A Dynamic Interpretation
16.6 Global Interpolation
16.7 Dealing with Trajectories
16.8 Conclusions

Part VI Applications to Engineering and Physics

Chapte 17
Objects in Contact: Boundary Collisions as Geometric Wave Propagation
Leo Dorst
17.1 Introduction
17.2 Boundary Geometry
17.3 The Boundary as a Geometric Object
17.4 Wave Propagation of Boundaries
17.5 Conclusions

Chapter 18 Modern Geometric Calculations in Crystallography
G. Aragon, J.L. Aragon, F. Davila, A. Gomez and M.A. Rodriguez
18.1 Introduction
18.2 Quasicrystals
18.3 The Morphology of Icosahedral Quasicrystals
18.4 Coincidence Site Lattice Theory
18.5 Conclusions

Chapter 19 Quaternion Optimization Problems in Engineering
Ljudmila Meister
19.1 Introduction
19.2 Properties of Quaternions
19.3 Extremal Problems for Quaternions
19.4 Determination of Rotations
19.5 The Main Problem of Orientation
19.6 Optimal Filtering and Prediction
19.7 Summary

Chapter 20
Clifford Algebras in Electrical Engineering
William Baylis
20.1 Introduction
20.2 Structure of Cl_3
20.3 Paravector Model of Spacetime
20.4 Using Relativity at Low Speeds
20.5 Relativity at High Speeds
20.6 Conclusions

Chapter 21
Applications of Geometric Algebra in Physics and Links With Engineering
Anthony Lasenby and Joan Lasenby

21.1 Introduction
21.2 The Spacetime Algebra
21.3 Quantum Mechanics
21.4 Gravity as a Gauge Theory
21.5 A New Representation of 6-d Conformal Space
21.6 Summary and Conclusions

Part VII Computational Methods in Clifford Algebras

Chapter 22
Clifford Algebras as Projections of Group Algebras
Vladimir M. Chernov
22.1 Introduction
22.2 Group Algebras and Their Projection
22.3 Applications
22.4 Conclusion

Chapter 23
Counterexamples for Validation and Discovering of New Theorems
Pertti Lounesto
23.1 Introduction
23.2 The Role of Counterexamples in Mathematics
23.3 Clifford Algebras: An Outline
23.4 Preliminary Counterexamples in Clifford Algebras
23.5 Counterexamples About Spin Groups
23.6 Counterexamples on the Internet


Chapter 24
The Making of GABLE: A Geometric Algebra Learning Environment in Matlab
Stephen Mann, Leo Dorst, and Tim Bouma
24.1 Introduction
24.2 Representation of Geometric Algebra
24.3 Inverses
24.4 Meet and Join
24.5 Graphics
24.6 Example: Pappus's Theorem
24.7 Conclusions

Chapter 25
Helmstetter Formula and Rigid Motions with CLIFFORD
Rafal Ablamowicz
25.1 Introduction
25.2 Verification of the Helmstetter Formula
25.3 Rigid Motions with Clifford Algebras
25.4 Summary



References



Index
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