Nonlinear Real-Time Optical Signal Processing

Abstract

During the period 1 July 1984-31 January 1990, the research under Grant AFOSR-84-0181 has been concerned with binary parallel optical computing architectures with particular attention to cellular logic and symbolic substitution for pattern recognition and numerical operations. Our approach has been to experimentally implement binary optical cellular logic processors and interconnection arrays; define an instruction set and software suited to optical computing systems; and to study generalizations of optical cellular logic processors such as the cellular hypercube. The results include the experimental implementation of a 54-gate binary optical cellular logic processor with instruction decoders, input/output, memory and test/branch functions; the completion of a binary image algebra (BIA) description of cellular logic, image analysis and symbolic operations; and the development of binary image algebra algorithms for scale and shift invariant patterns recognition. Additional work concerns the relationship of parallel computation paradigms to optical computing and halftone screen techniques for implementing general nonlinear functions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1990
Accession Number
ADA232889

Entities

People

  • A. A. Sawchuk

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automata
  • Automata Theory
  • Computations
  • Computer Architecture
  • Computer Programming
  • Electrical Engineering
  • Image Processing
  • Instruction Set Architecture
  • Modulation
  • Parallel Computing
  • Parallel Processing
  • Pattern Recognition
  • Signal Processing
  • Three Dimensional
  • Two Dimensional

Readers

  • Computer Programming and Software Development.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Nanoscale Plasmonic Nanotechnology

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms