The present work is the first volume of a substantially enlarged version of the mimeographed notes of a course of lectures first given by me in the Indian Statistical Institute, Calcutta, India, during 1964-65.
This volume records the lectures given at a NATO Advanced Study Institute on Methods in Computational Molecular Physics held in Bad Windsheim, Germany, from 22nd July until 2nd.
Nature is full of spidery patterns: lightning bolts, coastlines, nerve cells, termite tunnels, bacteria cultures, root systems, forest fires, soil cracking, river deltas, galactic distributions, mountain ranges, tidal patterns, cloud shapes, sequencing of nucleotides in DNA, cauliflower, broccoli, lungs, kidneys, the scraggly nerve cells that carry signals to and from your brain, the branching arteries and veins that make up your circulatory system.
Physics-Based Deformable Models presents a systematic physics-based framework for modeling rigid, articulated, and deformable objects, their interactions with the physical world, and the estimate of their shape and motion from visual data.
At present, there is an increasing interest in the prediction of properties of classical and new materials such as substitutional alloys, their surfaces, and metallic or semiconductor multilayers.
Neural Networks and Fuzzy Systems: Theory and Applications discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems.
Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms is an organized edited collection of contributed chapters covering basic principles, methodologies, and applications of fuzzy systems, neural networks and genetic algorithms.
This volume of research papers comprises the proceedings of the first International Conference on Mathematics of Neural Networks and Applications (MANNA), which was held at Lady Margaret Hall, Oxford from July 3rd to 7th, 1995 and attended by 116 people.
Nonlinear Modeling: Advanced Black-Box Techniques discusses methods on Neural nets and related model structures for nonlinear system identification; Enhanced multi-stream Kalman filter training for recurrent networks; The support vector method of function estimation; Parametric density estimation for the classification of acoustic feature vectors in speech recognition; Wavelet-based modeling of nonlinear systems; Nonlinear identification based on fuzzy models; Statistical learning in control and matrix theory; Nonlinear time-series analysis.
The subject of this book is predictive modular neural networks and their ap- plication to time series problems: classification, prediction and identification.
Neurobiology research suggests that information can be represented by the location of an activity spot in a population of cells (`place coding'), and that this information can be processed by means of networks of interconnections.
Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception.
The motion of a particle in a random potential in two or more dimensions is chaotic, and the trajectories in deterministically chaotic systems are effectively random.
Over the past decade high performance computing has demonstrated the ability to model and predict accurately a wide range of physical properties and phenomena.
Over the last thirty years or so, the attempts to identify the electronic origins of materials properties have proceeded along two distinct and apparently divergent methodologies.
Mixing may be thought of as the operation by which a system evolves from one state of simplicity (initial segregation) to another state of simplicity (complete uniformity).
Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns.
Stochastic Resonance: Theory and Applications deals with the theory of noise-added systems and in particular with Stochastic Resonance, a quite novel theory that was introduced in the 1980s to provide better understanding of some natural phenomena (e.
Enabling Technologies for Computational Science assesses future application computing needs, identifies research directions in problem-solving environments (PSEs), addresses multi-disciplinary environments operating on the Web, proposes methodologies and software architectures for building adaptive and human-centered PSEs, and describes the role of symbolic computing in scientific and engineering PSEs.
This volume contains a collection of review articles that are extended versions of invited lectures given at the First Pamporovo Winter Workshop on Cooperative Phe- nomena in Condensed Matter held in villa "e;Orlitza"e; (7th-15th March 1998, Pamporovo Ski Resort, Bulgaria).
This volume contains the proceedings of an International Conference on "e;Spin and Isospin in Nuclear Interactions"e;, which was held in Telluride, Colorado USA, 11-15 March 1991.
Quantum mechanics and quantum field theory on one hand and Gravity as a theory of curved space-time on the other are the two great conc- tual schemes of modern theoretical physics.
The present volume contains the texts of the invited talks delivered at the Sixth International Conference on Recent Progress in Many-Body Theories held in Arad, Israel during the period November 5-10 1989.
From August 21 through August 27, 1989 the Nato Advanced Research Workshop Probabilistic Methods in Quantum Field Theory and Quantum Gravity"e; was held at l'Institut d'Etudes Scientifiques, Cargese, France.
