Survey of Neural Net Paradigms for Specification of Discrete Networks.

Abstract

Innovative neural network architectures are seen as promising breakthroughs in key problems of interest in image and speech recognition, knowledge base coding and pattern classification. Cost characteristics dictate further research into massively parallel architectures. A survey of some salient characteristics of various paradigms is undertaken in the hope of extracting key underlying organizing principles. There are critiques of continuous-type systems, comments on noise, and some cognitive perspectives for discrete networks. There is a brief discussion of memory function. Some stochastic and functional outlines are given. Keywords: Cognition; Stochastic processes; Neural networks; Information theory; Discrete networks.

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Document Details

Document Type
Technical Report
Publication Date
Jan 31, 1988
Accession Number
ADA192682

Entities

People

  • Michael Dvorak

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Automata Theory
  • Cognition
  • Cognitive Science
  • Computer Languages
  • Computer Programming
  • Computer Vision
  • Image Recognition
  • Information Processing
  • Information Science
  • Network Science
  • Neural Networks
  • Object Recognition
  • Pattern Recognition
  • Random Variables
  • Security
  • Self Organizing Systems
  • Two Dimensional

Readers

  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks