This is a collection of outstanding review papers on integrable systems. It gives the algebraic geometric aspects of the subject, describes integrability techniques e.g. for the modified KdV equation, integrability of Hamiltonian systems, hierarchies of equations, probability distribution of eigenvalues, and modern aspects of quantum groups. It addresses researchers in mathematics and mathematical physics.

Rotor dynamics is an important branch of dynamics that deals with behavior of rotating machines ranging from very large systems like power plant rotors, for example, a turbogenerator, to very small systems like a tiny dentist's drill, with a variety of rotors such as pumps, compressors, steam/gas turbines, motors, turbopumps etc. as used for example in process industry, falling in between. The speeds of these rotors vary in a large range, from a few hundred RPM to more than a hundred thousand RPM. Complex systems of rotating shafts depending upon their specific requirements, are supported on different types of bearings. There are rolling element bearings, various kinds of fluid film bearings, foil and gas bearings, magnetic bearings, to name but a few. The present day rotors are much lighter, handle a large amount of energy and fluid mass, operate at much higher speeds, and therefore are most susceptible to vibration and instability problems. This have given rise to several interesting physical phenomena, some of which are fairly well understood today, while some are still the subject of continued investigation. Research in rotor dynamics started more than one hundred years ago. The progress of the research in the early years was slow. However, with the availability of larger computing power and versatile measurement technologies, research in all aspects of rotor dynamics has accelerated over the past decades. The demand from industry for light weight, high performance and reliable rotor-bearing systems is the driving force for research, and new developments in the field of rotor dynamics.

The symposium proceedings contain papers on various important aspects of rotor dynamics such as, modeling, analytical, computational and experimental methods, developments in bearings, dampers, seals including magnetic bearings, rub, impact and foundation effects, turbomachine blades, active and passive vibration control strategies including control of instabilities, nonlinear and parametric effects, fault diagnostics and condition monitoring, and cracked rotors.

This volume is of immense value to teachers, researchers in educational institutes, scientists, researchers in R&D laboratories and practising engineers in industry. "

- Models of vibro-impact systems are widely used in machine dynamics, vibration engineering, and structural mechanics. - Only monograph on this subject in English language. - Systematically presents the theory of vibro-impact systems by analysis of typical engineering applications. - Experimental data and computer simulations are presented. - Targeted to engineers and researchers in design and investigation of mechanical systems as well as to lecturers and advanced students.

In this book, a number of the world's leading researchers in quantum, classical and atomic physics cooperate to present an up-to-date account of the recent progress in the field. The first part highlights the latest advances in semiclassical theory, whilst the second one is devoted to applications to atomic systems. The authors present the material in pedagogical form to make it easy reading for non-specialists, too. Among the topics treated, the reader will find a new quasiclassical quantization scheme for Hamiltonian dynamics, an application of the semiclassical formalism to photodissociation of small molecules and to the Lorentz gas and discussions of tunneling corrections. Furthermore, one finds papers on chaotic ionization, on the behaviour of hydrogen atoms in external fields, e.g. magnetic or microwave fields.

In this book the concept of indistinguishability is defined for identical particles by the symmetry of the state. It applies, therefore, to both the classical and the quantum framework. The author describes symmetric statistical operators and classifies these by means of extreme points. For the description of infinitely extendible interchangeable random variables de Finetti's theorem is derived and generalizations covering the Poisson limit and the central limit are presented. A characterization and interpretation of the integral representations of classical photon states in quantum optics are derived in abelian subalgebras. Unextendible indistinguishable particles are analyzed in the context of nonclassical photon states. The book addresses mathematical physicists and philosophers of science.

The accomplishments and the available expertise of scientists working on spin systems, lattice gauge models, and quantum liquids and solids has culminated in an extraordinary opportunity for rapid and efficient development of realistic strategies and algorithms of ab initio theoretical analysis of conventional and exotic condensed-matter systems. This volume presents the latest results in the interdisciplinary field of lattice many-body systems. These include magnetism and phase transitions and lattice gauge problems in quantum field theory. Also treated are strongly correlated systems that help to unify many-body problems in solid-state physics, crystallography, and materials sciences and that helped their quantitative understanding.

In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. Neural networks are computing systems characterised by the ability to learn from examples rather than having to be programmed in a conventional sense. Their use enables the behaviour of complex systems to be modelled and predicted and accurate control to be achieved through training, without a priori information about the systems' structures or parameters. This book describes examples of applications of neural networks In modelling, prediction and control. The topics covered include identification of general linear and non-linear processes, forecasting of river levels, stock market prices and currency exchange rates, and control of a time-delayed plant and a two-joint robot. These applications employ the major types of neural networks and learning algorithms. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network. In addition, cerebellar-model-articulation-controller (CMAC) networks and neuromorphic fuzzy logic systems are also presented. The main learning algorithm adopted in the applications is the standard backpropagation (BP) algorithm. Widrow-Hoff learning, dynamic BP and evolutionary learning are also described.

Structural Phase Transitions II, like its predecessor (Topics in Current Physics, Vol. 23), presents selected methods and recent advances in the experimental investigation of phase transitions in solids. The two chapters in this volume deal with electron paramagnetic resonance (EPR), and with nuclear magnetic and nuclear quadrupole resonance (NMR-NQR). Both techniques are particularly sensitive to local properties. The chapter on EPR concentrates largely on the investigation of static properties, including mean-field behaviour, critical and multicritical phenomena, whilst NMR is shown to be a powerful tool for studying nonlinear dynamics, incommensurate transitions, and disordered systems. This book will serve as an excellent introduction to the methodology and applications of EPR and NMR-NQR for all those wishing to become acquainted with these important tools for studying structural phase transitions.

Stochastic Dynamics, born almost 100 years ago with the early explanations of Brownian motion by physicists, is nowadays a quickly expanding field of research within nonequilibrium statistical physics. The present volume provides a survey on the influence of fluctuations in nonlinear dynamics. It addresses specialists, although the intention of this book is to provide teachers and students with a reliable resource for seminar work. In particular, the reader will find many examples illustrating the theory as well as a host of recent findings.

This book introduces the novel concept of a fuzzy network whose nodes are rule bases and the connections between the nodes are the interactions between the rule bases in the form of outputs fed as inputs. The concept is presented as a systematic study for improving the feasibility and transparency of fuzzy models by means of modular rule bases whereby the model accuracy and efficiency can be optimised in a flexible way. The study uses an effective approach for fuzzy rule based modelling of complex systems that are characterised by attributes such as nonlinearity, uncertainty, dimensionality and structure.The approach is illustrated by formal models for fuzzy networks, basic and advanced operations on network nodes, properties of operations, feedforward and feedback fuzzy networks as well as evaluation of fuzzy networks. The results are demonstrated by numerous examples, two case studies and software programmes within the Matlab environment that implement some of the theoretical methods from the book. The book shows the novel concept of a fuzzy network with networked rule bases as a bridge between the existing concepts of a standard fuzzy system with a single rule base and a hierarchical fuzzy system with multiple rule bases.

Neural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is not only for the novice reader, but for experts in a variety of areas including parallel computing, neural network computing, computer science, communications, graph theory, computer aided design for VLSI circuits, molecular biology, management science, and operations research. The goal of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. Neural Network Parallel Computing presents a major breakthrough in science and a variety of engineering fields. The computational power of neural network computing is demonstrated by solving numerous problems such as N-queen, crossbar switch scheduling, four-coloring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling. Neural Network Parallel Computing is an excellent reference for researchers in all areas covered by the book. Furthermore, the text may be used in a senior or graduate level course on the topic.

Current companies and communities of practice are involved in intensive networking and collaborative systems by a great variety of electronic relations and collaborative interactions. This has resulted in entangled systems that need to be managed efficiently and in an autonomous way, thus facing many issues and challenges. The extensive research produced in this book will help virtual organizations to exploit latest and powerful technologies based on Grid and Wireless infrastructures as well as Cloud computing in order to alleviate complex issues and challenges arisen in networking and collaborative systems, in terms of collaborative applications, resource management, mobility, and security and system resilience. The ultimate aim of the book is to stimulate research that leads to the creation of responsive environments for networking and, at longer-term, the development of adaptive, secure, mobile, and intuitive intelligent systems for collaborative work and learning. Academic researchers, professionals and practitioners in the field will be inspired and put in practice the ideas and experiences proposed in the book in order to evaluate them for their specific research and work.

Modern achievements in the intensively developing field of applied mathematics are presented in this monograph. In particular, it proposes a new approach to extremal problem theory for nonlinear operators, differential-operator equations and inclusions, and for variational inequalities in Banach spaces. An axiomatic study of nonlinear maps (including multi-valued ones) is given, and the properties of resolving operators for systems, consisting of operator and differential-operator equations, are stated in nonlinear-map terms. The solvability conditions and the properties of extremal problem solutions are obtained, while their weak expansions and necessary conditions of optimality in variational inequality form are formulated. In addition. the monograph proposes regularization methods and approximation schemes. This book is adressed to scientists, graduates and undergraduates who are interested in nonlinear analysis, control theory, system analysis and differential equations.

Fuzzy Set Theory and Advanced Mathematical Applications contains contributions by many of the leading experts in the field, including coverage of the mathematical foundations of the theory, decision making and systems science, and recent developments in fuzzy neural control. The book supplies a readable, practical toolkit with a clear introduction to fuzzy set theory and its evolution in mathematics and new results on foundations of fuzzy set theory, decision making and systems science, and fuzzy control and neural systems. Each chapter is self-contained, providing up-to-date coverage of its subject. Audience: An important reference work for university students, and researchers and engineers working in both industrial and academic settings.

This book illustrates how models of complex systems are built up and provides indispensable mathematical tools for studying their dynamics. This second edition includes more recent research results and many new and improved worked out examples and exercises.

Since the late 1960s, there has been a revolution in robots and industrial automation, from the design of robots with no computing or sensorycapabilities (first-generation), to the design of robots with limited computational power and feedback capabilities (second-generation), and the design of intelligent robots (third-generation), which possess diverse sensing and decision making capabilities. The development of the theory of intelligent machines has been developed in parallel to the advances in robot design. This theory is the natural outcome of research and development in classical control (1950s), adaptive and learning control (1960s), self-organizing control (1970s) and intelligent control systems (1980s). The theory of intelligent machines involves utilization and integration of concepts and ideas from the diverse disciplines of science, engineering and mathematics, and fields like artificial intelligence, system theory and operations research. The main focus and motivation is to bridge the gap between diverse disciplines involved and bring under a common cover several generic methodologies pertaining to what has been defined as machine intelligence. Intelligent robotic systems are a specific application of intelligent machines. They are complex computer controlled robotic systems equipped with a diverse set of visual and non visual sensors and possess decision making and problem solving capabilities within their domain of operation. Their modeling and control is accomplished via analytical and heuristic methodologies and techniques pertaining to generalized system theory and artificial intelligence. Intelligent Robotic Systems: Theory, Design and Applications, presents and justifies the fundamental concepts and ideas associated with the modeling and analysis of intelligent robotic systems. Appropriate for researchers and engineers in the general area of robotics and automation, Intelligent Robotic Systems is both a solid reference as well as a text for a graduate level course in intelligent robotics/machines.

also in: THE KLUWER INTERNATIONAL SERIES ON ASIAN STUDIES IN COMPUTER AND INFORMATION SCIENCE, Volume 2

This book contains the lectures given at the NATO ASI 910820 "Cellular Automata and Cooperative Systems" Meeting which was held at the Centre de Physique des Houches, France, from June 22 to July 2, 1992. This workshop brought together mathematical physicists, theoretical physicists and mathe maticians working in fields related to local interacting systems, cellular and probabilistic automata, statistical physics, and complexity theory, as well as applications of these fields. We would like to thank our sponsors and supporters whose interest and help was essential for the success of the meeting: the NATO Scientific Affairs Division, the DRET (Direction des Recherches, Etudes et Techniques), the Ministere des Affaires Etrangeres, the National Science Foundation. We would also like to thank all the secretaries who helped us during the preparation of the meeting, in particular Maryse Cohen-Solal (CPT, Marseille) and Janice Nowinski (Courant Institute, New York). We are grateful for the fine work of Mrs. Gladys Cavallone in preparing this volume."

The Dynamics of Digital Excitation provides a fundamental new viewpoint on circuit therapy. It begins with a very real and practical problem and then presents arguments that are set forth for the first time. The most commonly used parameter of digital circuits, the gate delay time, does not exist. This problem emerges most clearly in the high-speed CMOS, above 1 GHz clock frequency. This book explains why that is so and then how to deal with the situation in a practical manner. Most of the large IC companies, and many of the small IC design companies, are now racing to capture above 1 GHz clock CMOS IC markets. A few examples of such companies in the United States are Motorola, Intel and DEC. Numerous new small design-only companies are also interested in this technology. The above 1 GHz circuit design is an extremely difficult concept and, for the designers, the material discussed in this book is indispensable. The Dynamics of Digital Excitation shows that the fastest CMOS circuits can be understood and designed only after understanding their quantum-mechanical nature.The Dynamics of Digital Excitation will help the circuit designer to learn how to deal with the problems of circuit delay when the gate delay is not a valid concept at high switching speeds and how to design the fastest critical paths. This book outlines essential and fundamental guidelines for designing the fastest CMOS circuits. It also explains how to design and structure computer-aided designs to deal with above 1 GHz circuits. The Dynamics of Digital Excitation sets forth exciting new ideas and will be of interest to IC designers and CAD professionals alike.

This self-contained treatment covers all aspects of nonlinear dynamics, from fundamentals to recent developments, in a unified and comprehensive way. Numerous examples and exercises will help the student to assimilate and apply the techniques presented.

Computer Simulation in Chemical Physics contains the proceedings of a NATO Advanced Study Institute held at CORISA, Alghero, Sardinia, in September 1992. In the five years that have elapsed since the field was last summarized there have been a number of remarkable advances which have significantly expanded the scope of the methods. Good examples are the Car--Parrinello method, which allows the study of materials with itinerant electrons; the Gibbs technique for the direct simulation of liquid--vapor phase equilibria; the transfer of scaling concepts from simulations of spin models to more complex systems; and the development of the configurational--biased Monte-Carlo methods for studying dense polymers. The field has also been stimulated by an enormous increase in available computing power and the provision of new software. All these exciting developments, an more, are discussed in an accessible way here, making the book indispensable reading for graduate students and research scientists in both academic and industrial settings.

This book, the first in a series on this subject, is the outcome of many years of efforts to give a new all-encompassing approach to complex systems in nature based on chaos theory. While maintaining a high level of rigor, the authors avoid an overly complicated mathematical apparatus, making the book accessible to a wider interdisciplinary readership.

Non-Destructive Evaluation (NDE) is now playing an increasing role in our modern global economy; in security sensitive industries, for instance. The complexity of the inspection task and either large or limited lot runs now require more operator-assisted or fully- automated signal processing. This book deals with both fields of expertise: NDE and signal processing. On the signal processing side, in the particular context of NDE applications, the following topics are discussed: sensor fusion, signal knowledge representation, artificial intelligence, fuzzy logic, computer vision, integration of numeric and non-numeric informations, parallel decomposition, noise processing and calibration of sensor devices as well as reliability of detection. Some hardware considerations are introduced as well, to discuss platforms on which processing is done. On the NDE side, applications include advances in holographic interferometry, microwave resonance or shearography and also on more traditional NDE techniques such as ultrasonics, infrared techniques, X-ray, computed tomography, Eddy currents. Inverse problems are also discussed. This book is required reading for those who already have some experience in one or both fields (signal processing and/or NDE).

Hybrid Intelligent Systems summarizes the strengths and weaknesses of five intelligent technologies: fuzzy logic, genetic algorithms, case-based reasoning, neural networks and expert systems, reviewing the status and significance of research into their integration. Engineering and scientific examples and case studies are used to illustrate principles and application development techniques. The reader will gain a clear idea of the current status of hybrid intelligent systems and discover how to choose and develop appropriate applications. The book is based on a thorough literature search of recent publications on research and development in hybrid intelligent systems; the resulting 50-page reference section of the book is invaluable. The book starts with a summary of the five major intelligent technologies and of the issues in and current status of research into them. Each subsequent chapter presents a detailed discussion of a different combination of intelligent technologies, along with examples and case studies. Four chapters contain detailed case studies of working hybrid systems.The book enables the reader to: * Describe the important concepts, strengths and limitations of each technology; * Recognize and analyze potential problems with the application of hybrid systems; * Choose appropriate hybrid intelligent solutions; * Understand how applications are designed with any of the approaches covered; * Choose appropriate commercial development shells or tools. An invaluable reference source for those who wish to apply intelligent systems techniques to their own problems.

Computation in Neurons and Neural Systems contains the collected papers of the 1993 Conference on Computation and Neural Systems which was held between July 31--August 7, in Washington, DC. These papers represent a cross-section of the state-of-the-art research work in the field of computational neuroscience, and includes coverage of analysis and modeling work as well as results of new biological experimentation.