A Novel Global Robust Stability Criterion for Neural Networks With Delay
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Date
2005
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Science Bv
Open Access Color
Green Open Access
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Top 10%
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Top 10%
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Abstract
A criterion based on the intervalised network parameters for the global robust stability of Hopfield-type neural networks with delay is presented. The criterion is compared with an earlier criterion. (c) 2005 Elsevier B.V. All rights reserved.
Description
Keywords
dynamical interval neural networks, equilibrium analysis, global robust stability, Hopfield neural networks, neural networks, Stability theory of functional-differential equations, Robust stability, Neural networks for/in biological studies, artificial life and related topics, equilibrium analysis, Hopfield neural networks, dynamical interval neural networks, neural networks, Qualitative investigation and simulation of models involving functional-differential equations, Neural nets applied to problems in time-dependent statistical mechanics, global robust stability
Turkish CoHE Thesis Center URL
Fields of Science
0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences
Citation
WoS Q
Q2
Scopus Q
OpenCitations Citation Count
39
Source
Physics Letters A
Volume
337
Issue
4-6
Start Page
369
End Page
373
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CrossRef : 38
Scopus : 47
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SCOPUS™ Citations
47
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Web of Science™ Citations
42
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1
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