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Global Stability Analysis of Neural Networks with Constant Time Delay via Frobenius Norm
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posted on 2020-01-01, 00:00 authored by N M Thoiyab, P Muruganantham, G Rajchakit, N Gunasekaran, B Unyong, U Humphries, P Kaewmesri, Chee Peng LimChee Peng LimThis paper deals with the global asymptotic robust stability (GARS) of neural networks (NNs) with constant time delay via Frobenius norm. The Frobenius norm result has been utilized to find a new sufficient condition for the existence, uniqueness, and GARS of equilibrium point of the NNs. Some suitable Lyapunov functional and the slope bounded functions have been employed to find the new sufficient condition for GARS of NNs. Finally, we give some comparative study of numerical examples for explaining the advantageous of the proposed result along with the existing GARS results in terms of network parameters.
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Journal
Mathematical Problems in EngineeringVolume
2020Article number
4321312Pagination
1 - 14Publisher
HindawiLocation
London, Eng.Publisher DOI
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1024-123XeISSN
1563-5147Language
EnglishPublication classification
C1 Refereed article in a scholarly journalUsage metrics
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