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Neural Networks
Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.
The Physics of Structure Formation
The formation and evolution of complex dynamical structures is one of the most exciting areas of nonlinear physics. Such pattern formation problems are common in practically all systems involving a large number of interacting components. Here, the basic problem is to understand how competing physical forces can shape stable geometries and to explain why nature prefers just these. Motivation for the intensive study of pattern formation phenomena during the past few years derives from an increasing appreciation of the remarkable diversity of behaviour encountered in nonlinear systems and of universal features shared by entire classes of nonlinear processes. As physics copes with ever more ambi...
Statistical Physics and Economics
This systematic book covers in simple language the physical foundations of evolution equations, stochastic processes and generalized Master equations applied on complex economic systems, helping to understand the large variability of financial markets, trading and communications networks.
Chemistry and Physics of One-Dimensional Metals
tailor-made molecules and indicated what kind of compounds could be prepared in the near future. In several evening and weekend sessions some participants presented summaries of their recent work and these and other new results were discussed. A draft of these discussions could not be added in printed form because of the 1 imitations set by the total page number of this volume, but to give at least an idea of the problems touched upon during these sessions, a 1 ist of the main contributors together with the title of the conribution discussed is given as an appendix. The reader might contact these authors directly if interested in special recent results. I hope that the participants have prof...
Organic Superconductors
The initial impetus for the search for an organic superconductor was the proposal of the existence of a polymer superconductor with a high critical temperature (Tc). This spurred on activities having the aim of synthesizing and characterizing organic conductors, which had already been going on for two decades. These efforts have resulted in the thriving field of low dimensional conductors and superconductors. This monograph is intended to be an introduction to and review of the study of organic conductors and superconductors. The investigations are to warrant a treatise of some length. At the same time sufficiently rich they have produced a few active subfields, each containing exciting topi...
Theory of Neural Information Processing Systems
Theory of Neural Information Processing Systems provides an explicit, coherent, and up-to-date account of the modern theory of neural information processing systems. It has been carefully developed for graduate students from any quantitative discipline, including mathematics, computer science, physics, engineering or biology, and has been thoroughly class-tested by the authors over a period of some 8 years. Exercises are presented throughout the text and notes on historical background and further reading guide the student into the literature. All mathematical details are included and appendices provide further background material, including probability theory, linear algebra and stochastic processes, making this textbook accessible to a wide audience.
Cooperative Dynamics in Complex Physical Systems
Many novel cooperative phenomena found in a variety of systems studied by scientists can be treated using the uniting principles of synergetics. Examples are frustrated and random systems, polymers, spin glasses, neural networks, chemical and biological systems, and fluids. In this book attention is focused on two main problems. First, how local, topological constraints (frustrations) can cause macroscopic cooperative behavior: related ideas initially developed for spin glasses are shown to play key roles also for optimization and the modeling of neural networks. Second, the dynamical constraints that arise from the nonlinear dynamics of the systems: the discussion covers turbulence in fluids, pattern formation, and conventional 1/f noise. The volume will be of interest to anyone wishing to understand the current development of work on complex systems, which is presently one of the most challenging subjects in statistical and condensed matter physics.
Synergetic Computers and Cognition
This book presents a novel approach to neural nets and thus offers a genuine alternative to the hitherto known neuro-computers. The new edition includes a section on transformation properties of the equations of the synergetic computer and on the invariance properties of the order parameter equations. Further additions are a new section on stereopsis and recent developments in the use of pulse-coupled neural nets for pattern recognition.
Spin Glasses and Complexity
Spin glasses are disordered magnetic systems that have led to the development of mathematical tools with an array of real-world applications, from airline scheduling to neural networks. Spin Glasses and Complexity offers the most concise, engaging, and accessible introduction to the subject, fully explaining what spin glasses are, why they are important, and how they are opening up new ways of thinking about complexity. This one-of-a-kind guide to spin glasses begins by explaining the fundamentals of order and symmetry in condensed matter physics and how spin glasses fit into--and modify--this framework. It then explores how spin-glass concepts and ideas have found applications in areas as d...
Models of Neural Networks I
One of the great intellectual challenges for the next few decades is the question of brain organization. What is the basic mechanism for storage of memory? What are the processes that serve as the interphase between the basically chemical processes of the body and the very specific and nonstatistical operations in the brain? Above all, how is concept formation achieved in the human brain? I wonder whether the spirit of the physics that will be involved in these studies will not be akin to that which moved the founders of the "rational foundation of thermodynamics". C. N. Yang! 10 The human brain is said to have roughly 10 neurons connected through about 14 10 synapses. Each neuron is itself ...
