Acceleration of Learning in Hybrid Neural Networks: A Novel Approach for the Design of Brain Chaosmakers

Abstract

Epileptic seizures correspond to episodes of increased rhythmicity of the normally chaotic activity in biological neural networks. We propose to use hybrid neural networks where artificial neural networks are used to control the biological neural networks by learning their different states. The learning is dramatically accelerated when using a conjugate gradient method in conjunction with the Fletcher-Reeves method of optimization.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409468

Entities

People

  • Alan Chiu
  • Berj L. Bardakjian

Organizations

  • University of Toronto

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Biomedical Engineering
  • Classification
  • Control Systems
  • Dynamics
  • Eigenvectors
  • Electronic Mail
  • Engineering
  • Epilepsy
  • Iterations
  • Learning
  • Military Research
  • Neural Networks
  • Optimization
  • Systems Biology
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Neuroscience
  • Operations Research

Technology Areas

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