Novel Results on Global Robust Stability Analysis for Dynamical Delayed Neural Networks Under Parameter Uncertainties

In this paper, we focus on the global stability analysis with respect to dynamical delayed neural networks (NNs) that contain parameter uncertainties. Many investigations on the sufficient conditions utilizing different upper bounds for the norm of interconnection matrices pertaining to the global a...

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Veröffentlicht in:	IEEE access Jg. 8; S. 178108 - 178116
Hauptverfasser:	Gunasekaran, Nallappan, Thoiyab, N. Mohamed, Muruganantham, P., Rajchakit, Grienggrai, Unyong, Bundit
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Asymptotic properties Delay effects Dynamic stability Dynamical delayed neural networks Functionals interval matrices Mathematical model Neural networks Neurons parameter uncertainties Parameter uncertainty Robust stability robust stability analysis Robustness (mathematics) slope bounded activation function Stability analysis Upper bound Upper bounds
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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