Parallel Processing in Neural Systems and Computers
Rolf Eckmiller, Georg Hartmann, Gert Hauske
North-Holland, 1990 - Computers - 626 pages
The 119 contributions in this book cover a range of topics, including parallel computing, parallel processing in biological neural systems, simulators for artificial neural networks, neural networks for visual and auditory pattern recognition as well as for motor control, AI, and examples of optical and molecular computing. The book may be regarded as a state-of-the-art report and at the same time as an Interdisciplinary Reference Source' for parallel processing. It should catalyze international and interdisciplinary cooperation among computer scientists, neuroscientists, physicists and engineers in the attempt to: 1) decipher parallel information processes in biology, physics and chemistry 2) design conceptually similar technical parallel information processors."
What people are saying - Write a review
We haven't found any reviews in the usual places.
Neuroinformatics and Cybernetics Invited Paper
Parallel Processing Using MemoryBased Connectionist Networks
Why Do Neural Network Researchers Ignore Stochastic Computers?
67 other sections not shown
Other editions - View all
activity adaptive algorithm allows analysis application approach architecture associative brain cells changes complex components Computer connections consists correlation corresponding coupling cycle defined delay depends described direction distribution dynamics Eckmiller Editors effect equations error example experiments field Figure frequency function given implemented increase initial input internal layer learning mapping matrix means mechanism memory method motion movement natural neural networks neurons object operations optimal orientation oscillators output parallel parameters patterns performance phase Physics position possible presented problem processing processors production properties Publishers random recognition REFERENCES representation represented Research respect response rule scheme Science selection sequence shown shows signal simple simulation single solution space step stimulus structure synapses synchronization task temporal theory units University values vector visual weights