Study on Extremizing Adaptive Systems and Applications to Synthetic Aperture Radars.

Abstract

For this study the application of Artificial Intelligence methods in synthetic aperture radars (SAR) is investigated. It was found that the neuron-like ASE-ACE adaptive algorithm developed by Bartis, operating in the extremizing mode suggested by Klopf, can be used in a wide class of engineering problems requiring that some performance function be minimized. One such suggested application is to correct for quadratic phase errors in SAR signal processing. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1983
Accession Number
ADA137725

Entities

People

  • D. T. Politis
  • W. H. Licata

Organizations

  • Environmental Research Institute of Michigan

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Computational Science
  • Control Systems
  • Coordinate Systems
  • Detectors
  • Differential Equations
  • Dynamics
  • Engineering
  • Learning
  • Line Of Sight
  • Radar
  • Robotics
  • Sampling
  • Simulations
  • Synthetic Aperture Radar

Fields of Study

  • Engineering

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Neural Network Machine Learning.
  • Radar Systems Engineering.

Technology Areas

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