Neural Computers

The soft cover study edition now available is a revised reprint of the successful first edition of 1988. It collects invited presentations of an Advanced Research Workshop on "Neural Computers", held in Neuss, Federal Republic of Germany, September 28 - O

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 with Noise: 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 all Contributions.- Reference Author Index.- List of Contributors.