التفاصيل البيبلوغرافية
| العنوان: |
Global Mittag-Leffler Stability and Global Asymptotic ω-Period for Fractional-Order Cohen–Grossberg Neural Networks with Time-Varying Delays. |
| المؤلفون: |
Jiang, Wangdong, Li, Zhiying, Zhang, Yuehong |
| المصدر: |
International Journal of Pattern Recognition & Artificial Intelligence; Sep2022, Vol. 36 Issue 12, p1-17, 17p |
| مصطلحات موضوعية: |
GLOBAL asymptotic stability, TIME-varying networks, FRACTIONAL calculus |
| مستخلص: |
The dynamic behaviors for fractional-order Cohen–Grossberg neural networks with time-varying delays (FCGNND) are studied in this paper. By introducing the Mittag-Leffler (ML) function, based on properties of fractional calculus, the differential mean-value theorem and Arzela–Ascoli theorem, we give some sufficient theorems to determine the boundedness, global Mittag-Leffler stability (GMLS) and global asymptotical ω -periodicity (GAP) for FCGNND. Finally, a numerical example is given to verify the effectiveness of the theorems. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
