Optoelectronic Realizations of Neural Network Models

Abstract

This research project is aimed at developing silicon based implementations of neural network models. The main advantages of our approach are its use of standard, present day technology and its highly memory due to the use of optics. Two different embodiments of the electronic part of the neural processor have been realized. A phototransistor based network using standard complementary metal oxide semiconductors technology has been built and tested. The CCD version of the optoelectronic architecture has been fabricated and tested, proving the viability of this architecture. All electronic loading has been explored and offers possibilities of rugged, compact systems. (KR)

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Document Details

Document Type
Technical Report
Publication Date
Oct 12, 1990
Accession Number
ADA228841

Entities

People

  • Aharon J. Agranat
  • Amnon Yariv
  • C. Neugebauer
  • V. Leyva

Organizations

  • California Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bipolar Junction Transistors
  • Clocks
  • Complementary Metal-Oxide Semiconductors
  • Computing System Architectures
  • Electronic Components
  • Electronics
  • Electronics Laboratories
  • Modules (Electronics)
  • Neural Networks
  • Photodetectors
  • Phototransistors
  • Semiconductor Devices
  • Semiconductors
  • Standards
  • Test Equipment
  • Transistors

Readers

  • Neural Network Machine Learning.
  • Semiconductor Device Technology
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Microelectronics