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 - October 2, 1987. The objectives of the workshop were - to promote international collaboration among scientists from the fields of Neuroscience, Computational Neuroscience, Cellular Automata, Artificial Intelligence, and Computer Design; and - to review our present knowledge of brain research and novel computers with neural network architecture. The workshop assembled some fifty invited experts from Europe, America and Japan representing the relevant fields. The book describes the transfer of concepts of brain function and brain architecture to the design of self-organizing computers with neural network architecture. The contributions 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 the contributions are review papers. In addition, group reports summarize the discussions regarding four specific topics relevant to the state of the art in neural computers. With its extensive reference list as well as its subject and name indexes this volume will serve as a reference book for future research in the field of Neural Computers.
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Faust Mephistopheles and Computer
Goal and Architecture of Neural Computers
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activity algorithm applications architecture array associative memory backpropagation behaviour Berlin Heidelberg 1988 biological Boltzmann machine brain cells chip circuit Computer Vision connectionist connections convergency coordinates cortex cortical distributed dynamics Eckmiller and Ch elements equation error example F41 Neural Computers feedback field function Hinton Hopfield IEEE implementation input interaction interconnection iteration label layer learning rule linear mapping mathematical matrix metric tensor minterms motor command movements NETSIM network model Neural Computers Edited neural networks neurocomputers neurons Neuroscience node nonlinear ooooooooooooooooooooooooo operation optical optical flow optimal output parallel parallel computers parameters pattern recognition Pellionisz perceptron perform pixels problem Proc processor receptive fields representation retinotopic robot saccade schemas segmentation Sejnowski selection sensory sequences shown signals simulation spatial Springer-Verlag Berlin Heidelberg storage stored structure synaptic systolic array tensor theory transputer units v. d. Malsburg values variables vector velocity vision visual visual cortex VLSI