Novel Global Robust Stability Criterion for Neural Networks With Delay
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Date
2009
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Pergamon-elsevier Science Ltd
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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Impulse
Top 10%
Influence
Top 10%
Popularity
Average
Abstract
A novel criterion for the global robust stability of Hopfield-type interval neural networks with delay is presented. An example illustrating the improvement of the present criterion over several recently reported criteria is given. (C) 2008 Elsevier Ltd. All rights reserved.
Description
Keywords
[No Keyword Available], 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
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
11
Source
Physics Letters A
Volume
41
Issue
1
Start Page
348
End Page
353
PlumX Metrics
Citations
CrossRef : 10
Scopus : 12
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Mendeley Readers : 6
SCOPUS™ Citations
12
checked on Mar 06, 2026
Web of Science™ Citations
13
checked on Mar 06, 2026
Page Views
2
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