Biomorphic Networks for ATR and Higher-Level Processing

Abstract

We introduce the concept of parametrically and nonlinearly coupled network of bifurcation processing elements that can be driven by static or dynamic input patterns. The network is biologically inspired, computes with all three types of attractors, and offers a unique tool for the modeling and study of cortical networks and higher level brain function.

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Document Details

Document Type
Technical Report
Publication Date
Jan 10, 1998
Accession Number
ADA336093

Entities

People

  • Nabil H. Farbat

Organizations

  • University of Pennsylvania

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Brain
  • Computer Simulations
  • Detectors
  • Electrical Engineering
  • Engineering
  • Frequency
  • Imaging Techniques
  • Magnetic Resonance
  • Magnetic Resonance Imaging
  • Magnetometers
  • Neural Networks
  • Neuroimaging
  • Pattern Recognition
  • Positron Emission Tomography
  • Simulations
  • Tomography
  • Visual Cortex

Readers

  • Control Systems Engineering.
  • Neural Network Machine Learning.