Topological Methods in Nonlinear Analysis

Global exponential stability and existence of anti-periodic solutions to impulsive Cohen-Grossberg neural networks on time scales

Yongkun Li and Tianwei Zhang

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Abstract

By using the method of coincidence degree theory and Lyapunov functions, some new criteria are established for the existence and global exponential stability of anti-periodic solutions to impulsive Cohen-Grossberg neural networks on time scales. Our results are new even if the time scale $\mathbb{T}=\mathbb{R}$ or $\mathbb{Z}$. Finally, an example is given to illustrate our results.

Article information

Source
Topol. Methods Nonlinear Anal., Volume 45, Number 2 (2015), 363-384.

Dates
First available in Project Euclid: 30 March 2016

Permanent link to this document
https://projecteuclid.org/euclid.tmna/1459343987

Digital Object Identifier
doi:10.12775/TMNA.2015.018

Mathematical Reviews number (MathSciNet)
MR3408827

Zentralblatt MATH identifier
1365.34126

Citation

Li, Yongkun; Zhang, Tianwei. Global exponential stability and existence of anti-periodic solutions to impulsive Cohen-Grossberg neural networks on time scales. Topol. Methods Nonlinear Anal. 45 (2015), no. 2, 363--384. doi:10.12775/TMNA.2015.018. https://projecteuclid.org/euclid.tmna/1459343987


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