Design and analysis of fixed planar holographic interconnects for optical neural networks

Paul E. Keller, Arthur F. Gmitro

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

A neural-network architecture of multifaceted planar interconnection holograms and optoelectronic neurons is analyzed. Various computer-generated hologram techniques are analyzed and tested for their ability to produce an interconnection hologram with high-accuracy interconnects and high diffraction efficiency. A new technique is developed by using the Gerchberg-Saxton algorithm, followed by a random-search error minimization that produces the highest interconnect accuracy and the highest diffraction efficiency of the techniques tested. Analysis of the system shows that the hologram has the capacity to connect 5000 neuron outputs to 5000 neuron inputs with bipolar synapses and that the encoded synaptic weights have an accuracy of ˜ 5 bits. A simple feedback system is constructed and demonstrated.

Original languageEnglish (US)
Pages (from-to)5517-5526
Number of pages10
JournalApplied optics
Volume31
Issue number26
DOIs
StatePublished - Sep 1992

Keywords

  • Computer-generated holograms
  • Multifaceted holograms
  • Neural networks
  • Optical computing
  • Optical interconnects

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering

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