Skip to main content
Article thumbnail
Location of Repository

A Simple Chaotic Neuron

By Frank Pasemann

Abstract

The discrete dynamics of a dissipative nonlinear model neuron with self-interaction is discussed. For units with self-excitatory connection hysteresis effects, i.e. bistability over certain parameter domains, are observed. Numerical simulations demonstrate that self-inhibitory units with non-zero decay rates exhibit complex dynamics including period doubling routes to chaos. These units may be used as basic elements for networks with higherorder information processing capabilities. appeared in: Physica D, 104, 205 - 211, 1997. 1 1 Introduction Biological neurons exhibit a large variety of dynamical behaviors even when they are not embedded in a network. This type of dynamics is captured by biologically inspired neuron models like the Hodgkin-Huxley [1] or the FitzHugh-Nagumo equations [2], [3]. On the other hand, formal neurons used in artificial neural networks like the McCulloch-Pitts neuron or the graded response neurons [4] have only trivial, i.e. convergent dynamics as s..

Year: 1997
OAI identifier: oai:CiteSeerX.psu:10.1.1.36.2440
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.theorielabor.de/FTP... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.