Temporal Processing with Neural Networks.

Abstract

The research carried out under this contract focussed on four efforts, all involving the processing of temporal sequences by neural networks (1-3) or the effect of imposing a spatio-temporal gradient on network learning (4): (1) Assessing alternative neural network techniques for problems involving temporal coding. (2) Development of tools for analysing recurrent networks, so that the solutions of successfully trained networks can be better understood; (3) Development of a dynamical systems theory approach to computation in recurrent networks. (4) Development of biologically and cognitively plausible techniques for enhancing training.

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Document Details

Document Type
Technical Report
Publication Date
Jun 25, 1998
Accession Number
ADA347549

Entities

People

  • Jeffrey L. Elman

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Brain
  • Cognition
  • Cognitive Science
  • Computations
  • Computer Programming
  • Computer Science
  • Data Sets
  • Flow Fields
  • Formal Languages
  • Grammars
  • Information Systems
  • Language
  • Linguistics
  • Neural Networks
  • Probability Distributions
  • Psychology
  • Training

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Instructional Design and Training Evaluation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks