An Application of Exponential Neural Networks to Event-Train Recognition.

Abstract

The purpose of this project is to investigate neural networks for specific applications in passive electronic warfare (EW) involving restoration of deinterleaved pulse trains to their original broadcast form. The project took a generic event-train approach and focused on event-train recognition. It was determined that back propagation neural networks did not represent a logistically supportable means of training. Gaussian radial basis functions were found to be far superior. This report is composed of three chapters: (1) summary of early experiments, (2) introduction to exponential neural networks, and (3) application to event-train recognition. Each chapter has its own references. We believe that the goal can be reached and that additional experiments, with greater data volumes, are warranted.

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Document Details

Document Type
Technical Report
Publication Date
May 08, 1992
Accession Number
ADA254948

Entities

People

  • Peter G. Raeth

Organizations

  • Wright Laboratory

Tags

Communities of Interest

  • Electronic Warfare
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Computational Science
  • Computers
  • Electrical Engineering
  • Electronic Countermeasures
  • Electronic Warfare
  • Expert Systems
  • Information Processing
  • Information Science
  • Knowledge Based Systems
  • Neural Networks
  • Parallel Processors
  • Pattern Recognition
  • Reliability
  • Self Organizing Systems
  • Three Dimensional

Readers

  • Neural Network Machine Learning.
  • Positioning, Navigation, and Timing (PNT) Technology.
  • Theoretical Analysis.

Technology Areas

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