the outcome of a NATO Advanced Research Workshop (ARW) This book is held in Neuss (near Dusseldorf), Federal Republic of Germany from 28 September to 2 October, 1987. The workshop assembled some 50 invited experts from Europe, Ameri ca, and Japan representing the fields of Neuroscience, Computational Neuroscience, Cellular Automata, Artificial Intelligence, and Compu ter Design; more than 20 additional scientists from various countries attended as observers. The 50 contributions in this book cover a wide range of topics, including: Neural Network Architecture, Learning and Memory, Fault Tolerance, Pattern Recognition, and Motor Control in Brains versus Neural Computers. Twelve of these contributions are review papers. The readability of this book was enhanced by a number of measures: * The contributions are arranged in seven chapters. * A separate List of General References helps newcomers to this ra pidly growing field to find introductory books. * The Collection of References from all Contributions provides an alphabetical list of all references quoted in the individual con tributions. * Separate Reference Author and Subject Indices facilitate access to various details. Group Reports (following the seven chapters) summarize the discus sions regarding four specific topics relevant for the 'state of the art' in Neural Computers.

Inhalt
1: Introductory Lectures.- The Role of Adaptive and Associative Circuits in Future Computer Designs.- Faust, Mephistopheles and Computer.- 2: Architecture and Topology of Neural Networks: Brain vs. Computer.- Structured Neural Networks in Nature and in Computer Science.- Goal and Architecture of Neural Computers.- 3: Fault Tolerance in Biological vs. Technical Neural Networks.- Conventional Fault-Tolerance and Neural Computers.- Fault-Tolerance in Imaging-Oriented Systolic Arrays.- Parallelism and Redundancy in Neural Networks.- 4: Visual Pattern Recognition Systems.- Relational Models in Natural and Artificial Vision.- Image Segmentation with Neurocomputers.- A Hierarchical Neural Network Model for Selective Attention.- Mapping Images to a Hierarchical Data Structure A Way to Knowledge-Based Pattern Recognition.- Computing Motion in the Presence of Discontinuities: Algorithm and Analog Networks.- Design Principles for a Front-End Visual System.- Towards a Primal Sketch of Real World Scenes in Early Vision.- Why Cortices? Neural Computation in the Vertebrate Visual System.- A Cortical Network Model for Early Vision Processing.- Image Segregation by Motion: Cortical Mechanisms and Implementation in Neural Networks.- On the Acquisition of Object Concepts from Sensory Data.- Neural Computers in Vision: Processing of High Dimensional Data.- Computational Networks in Early Vision: From Orientation Selection to Optical Flow.- 5: Learning and Memory in Neural Network Systems.- Logical Connectionist Systems.- Backpropagation in Perceptrons with Feedback.- A Neural Model with Multiple Memory Domains.- The Never-Ending Learning.- Storing Sequences of Biased Patterns in Neural Networks with Stochastic Dynamics.- The Inverse Problem for Linear Boolean Nets.- Training withNoise: Application to Word and Text Storage.- Of Points and Loops.- On the Asymptotic Information Storage Capacity of Neural Networks.- Learning Networks of Neurons with Boolean Logic.- Neural Network Learning Algorithms.- Exploring Three Possibilities in Network Design: Spontaneous Node Activity, Node Plasticity and Temporal Coding.- 6: Motor Program Generation and Sensorimotor Coordinate Transformation.- Schemas and Neurons: Two Levels of Neural Computing.- Applications of Concurrent Neuromorphic Algorithms for Autonomous Robots.- The Relevance of Mechanical Sensors for Neural Generation of Movements in Space.- Spatial and Temporal Transformations in Visuo-Motor Coordination.- Neural Networks for Motor Program Generation.- Innate and Learned Components in a Simple Visuo-Motor Reflex.- Tensor Geometry: A Language of Brains & Neurocomputers. Generalized Coordinates in Neuroscience & Robotics.- Extending Kohonen's Self-Organizing Mapping Algorithm to Learn Ballistic Movements.- 7: Parallel Computers and Cellular Automata.- Limited Interconnectivity in Synthetic Neural Systems.- Nonlinear Optical Neural Networks: Dynamic Ring Oscillators.- Dynamical Properties of a New Type of Neural Network.- A Dedicated Computer for Simulation of Large Systems of Neural Nets.- Neurocomputer Applications.- Asynchrony and Concurrency.- Implementation of Neural Network Models in Silicon.- The Transputer.- Parallel Architectures for Neural Computers.- Control of the Immune Response.- Group Report 1: Structure in Neural Networks.- Group Report 2: General Software for the Simulation of Neural Nets.- Group Report 3: Hardware (e.g. Transputer Based) for Neural Computing.- Group Report 4: Typical Applications of Neural Computers.- List of General References.- Collection of References from allContributions.- Reference Author Index.- List of Contributors.