Theoretical investigation of optical computing based on neural network models
Abstract
The optical implementation of weighted interconnections is investigated and basic relationship are derived between the number of neurons, the number of connections and methods for selecting the positions of the neurons to achieve the maximum density of independent connections are presented. The connectivity of a neural network (number of synapses per neuron) is related to the complexity of the problems it can handle. For a network that learns a problem from examples using a local learning rule, it is proved that the entropy of the problem becomes a lower bound for the connectivity of the network.
 Publication:

California Instute of Technology Technical Report
 Pub Date:
 November 1988
 Bibcode:
 1988cit..reptQ....P
 Keywords:

 Models;
 Network Analysis;
 Neural Nets;
 Optical Computers;
 Optical Data Processing;
 Circuits;
 Computation;
 Electric Connectors;
 Entropy;
 Neurons;
 Optical Paths;
 Weighting Functions;
 Optics