ARTIFICIAL NEURAL NETWORKS FOR COMPUTING.

L. D. Jackel, Richard Howard, H. P. Graf, B. Straughn, J. S. Denker

Research output: Contribution to journalArticle

19 Scopus citations

Abstract

Recent proposals for neural network models indicate that an array of amplifiers coupled to a lattice of wires with resistive components at the crosspoints can perform calculations using collective properties similar to those observed in biological systems. Such a network can perform both memory and processing functions. The promise of the connection matrix processor lies in its very high density, fault tolerance, and massively parallel operation. This paper describes the operation of a neural network and exploratory fabrication techniques for its implementation.

Original languageEnglish (US)
Pages (from-to)61-63
Number of pages3
JournalJournal of Vacuum Science and Technology B: Microelectronics and Nanometer Structures
Volume4
Issue number1
DOIs
StatePublished - Jan 1 1986
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Condensed Matter Physics
  • Electrical and Electronic Engineering

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