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
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Zusammenfassung: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 asymptotic robust stability of delayed NNs have been conducted. In this study, a new upper bound of the norm of connection weight matrices is derived for the delayed NNs under parameter uncertainties. The key focus is on how the new upper bound is able to yield minimum result with respects to some of the existing upper bounds. We demonstrate that the new upper bound can lead to some new sufficient conditions with respect to the global asymptotic robust stability of equilibrium point of the delayed NNs. The slope bounded activation functions and Lyapunov-Krasovskii functionals (LKFs) are employed for formulating the sufficient conditions of the equilibrium point of NNs. Moreover, the derived sufficient conditions are independent on the time delay parameter. Numerical examples are provided and the outcomes obtained are compared with those of the existing results subject to different network parameters.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3016743