A Biologically Inspired Neural Network Composed of Dissimilar Single Neuron Models

Abstract

A multilayer neural network has been developed that consists of slabs of single neuron models. Each slab is composed of a single type of neurons, which differs between the slabs. The network was trained using a biologically inspired, Hebbian-like, learning rule on EMG data and good training/testing classification performance was obtained. It was shown that the biologically inspired network, the novel architecture of which is derived from the functionally distinct hypercolumns of neurons in the brain, can be successfully applied on difficult classification tasks.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411416

Entities

People

  • C. C. Neocleous
  • C. N. Schizas
  • C. S. Pattichis
  • P. Poirazi

Organizations

  • University of Cyprus

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Annealing
  • Brain
  • Cells
  • Classification
  • Computer Science
  • Computers
  • Computing System Architectures
  • Data Displays
  • Engineering
  • Equations
  • Learning
  • Network Architecture
  • Neural Networks
  • Neurons
  • Training

Readers

  • Neural Network Machine Learning.
  • Neuroscience

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks