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Neural Correlation via Random Connections

Neural Correlation via Random Connections A simple neural network is studied, which has sparse, random, plastic, excitatory connections and also feedback loops between sensory cells and correlator cells. Time is limited to several discrete instants, where firing is synchronous. For parameter values within biological ranges, the system exhibits a capacity for associative recall, with a controlled amount of extraneous firing, following Hebb-like synaptic changes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neural Computation MIT Press

Neural Correlation via Random Connections

Neural Computation , Volume 8 (8) – Nov 1, 1996

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References (16)

Publisher
MIT Press
Copyright
© 1996 Massachusetts Institute of Technology
ISSN
0899-7667
eISSN
1530-888X
DOI
10.1162/neco.1996.8.8.1711
Publisher site
See Article on Publisher Site

Abstract

A simple neural network is studied, which has sparse, random, plastic, excitatory connections and also feedback loops between sensory cells and correlator cells. Time is limited to several discrete instants, where firing is synchronous. For parameter values within biological ranges, the system exhibits a capacity for associative recall, with a controlled amount of extraneous firing, following Hebb-like synaptic changes.

Journal

Neural ComputationMIT Press

Published: Nov 1, 1996

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