An Efficient, Wavelet Based, Variable Structure Network.

Abstract

Learning systems, specifically neural networks trained using supervised learning, have become widely accepted and in many cases provide good approximations to the given target function. One of the parameters that tends to make a large difference in the output of the network is its size, or number of units that comprise the network. However, there is often no easy way to determine how large a network should be. A way to combat this problem is through a variable structure algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1998
Accession Number
ADA358547

Entities

People

  • Chad A. Tilbury

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Computer Science
  • Computers
  • Equations
  • Fourier Analysis
  • Image Processing
  • Information Science
  • Neural Networks
  • Reinforcement Learning
  • Self Organizing Systems
  • Simulations
  • Statistics
  • Training
  • Two Dimensional
  • Wavelet Transforms

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Computer Vision.

Technology Areas

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