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Proceedings Paper

Neural Networks In Dynamical Systems
Author(s): K. S. Narendra; K. Parthasarathy
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Paper Abstract

Multilayer networks and recurrent neural networks have proved extremely successful in pattern recognition problems as well as in associative learning. In this paper an attempt is made to demonstrate that both types of networks, combined in arbitrary configurations, will find application in complex dynamical systems. Well known results in linear systems theory and their extensions to conventional adaptive control theory are used to suggest models for the identification and control of nonlinear dynamic systems. The use of neural networks in dynamical systems raises many theoretical questions, some of which are discussed in the paper.

Paper Details

Date Published: 1 February 1990
PDF: 12 pages
Proc. SPIE 1196, Intelligent Control and Adaptive Systems, (1 February 1990); doi: 10.1117/12.969922
Show Author Affiliations
K. S. Narendra, Yale University (United States)
K. Parthasarathy, Yale University (United States)

Published in SPIE Proceedings Vol. 1196:
Intelligent Control and Adaptive Systems
Guillermo Rodriguez, Editor(s)

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