Globally robust stability analysis for stochastic Cohen – Grossberg neural networks with impulse control and time-varying delays
By constructing suitable Lyapunov functionals, in combination with the matrix-inequality technique, a new simple sufficient linear matrix inequality condition is established for the globally robustly asymptotic stability of the stochastic Cohen – Grossberg neural networks with impulsive control and...
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| Datum: | 2017 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Institute of Mathematics, NAS of Ukraine
2017
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| Online Zugang: | https://umj.imath.kiev.ua/index.php/umj/article/view/1757 |
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| Назва журналу: | Ukrains’kyi Matematychnyi Zhurnal |
| Завантажити файл: |  |
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Ukrains’kyi Matematychnyi Zhurnal| Zusammenfassung: | By constructing suitable Lyapunov functionals, in combination with the matrix-inequality technique, a new simple sufficient
linear matrix inequality condition is established for the globally robustly asymptotic stability of the stochastic Cohen –
Grossberg neural networks with impulsive control and time-varying delays. This condition contains and improves some
previous results from the earlier references.
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