Chaotic dynamics of time-delay neural networks

Jose C. Principe*, Pei-Chen Lo

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

A study is made of the nonlinear dynamical properties of a class of recurrent artificial neural networks with time delay that have been proposed in the literature to learn and recognize time-varying input patterns. Their nonlinear dynamics are studied to see if they have the potential to model nonlinear dynamical behavior of biological field potentials such as the electroencephalogram (EEG). It is shown that changing the value of the weights in a periodic fashion causes the output of time-delay neural networks to show a correlation dimension in the EEG range.

Original languageEnglish
Pages403-409
Number of pages7
StatePublished - 1 Dec 1990
Event1990 International Joint Conference on Neural Networks - IJCNN 90 Part 3 (of 3) - San Diego, CA, USA
Duration: 17 Jun 199021 Jun 1990

Conference

Conference1990 International Joint Conference on Neural Networks - IJCNN 90 Part 3 (of 3)
CitySan Diego, CA, USA
Period17/06/9021/06/90

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