Singular perturbations and time scales in artificial neural networks

Kevin L. Moore, D. Subbaram Naidu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The learning and computing processes in a recursive neural network of the Hopfield type are identified as slow and fast phenomena. The corresponding dynamical equations are cast to fit into the framework of the theory of singular perturbations and time scales. The issues of degeneration and asymptotic expansions arising in obtaining approximate solutions are addressed.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Decision and Control
PublisherPubl by IEEE
Pages2932-2933
Number of pages2
ISBN (Print)0780304500
StatePublished - Dec 1 1991
EventProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3) - Brighton, Engl
Duration: Dec 11 1991Dec 13 1991

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume3
ISSN (Print)0191-2216

Other

OtherProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3)
CityBrighton, Engl
Period12/11/9112/13/91

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