Patent · US Expired

Neuromorphic learning networks

US4874963A · kind A · utility

108Cited by
8References
12Claims
0Family size

Assignee

Inventor

Key dates

Filing dateFeb 11, 1988
Grant dateOct 17, 1989
Priority date
Expiry dateFeb 11, 2008

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N3/063
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

A neuron network which achieves learning by means of a modified Boltzmann algorithm. The network may comprise interconnected input, hidden and output layers of neurons, the neurons being "on-off" or threshold electronic devices which are symmetrically connected by means of adjustable-weight synapse pairs. The synapses comprise the source-drain circuits of a plurality of paralleled FETs which differ in resistance or conductance in a binary sequence. The synapses are controlled by the output of an Up-Down counter, the reading of which is controlled by the results of a correlation of the states of the two neurons connected by the synapse pairs following the application of a set of plus and minus training signals to selected neurons of said network. A noise generator comprising a thermal noise source is provided for each neuron for the purpose of simulated annealing of the network.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.