| Issue |
MATEC Web Conf.
Volume 355, 2022
2021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
|
|
|---|---|---|
| Article Number | 02006 | |
| Number of page(s) | 6 | |
| Section | Mathematical Science and Application | |
| DOI | https://doi.org/10.1051/matecconf/202235502006 | |
| Published online | 12 January 2022 | |
Almost anti-periodic solution of inertial neural networks model on time scales
1 National School of Advanced Sciences and Technologies of Borj Cedria, University of Carthage, Tunisia
2 Laboratory of Engineering Mathematics (LR01ES13), Tunisia Polytechnic School, University of Carthage, Tunisia
* Corresponding author: adnen.arbi@enseignant.edunet.tn
In this work, since the importance of investigation of oscillators solutions, an methodology for proving the existence and stability of almost anti-periodic solutions of inertial neural networks model on time scales are discussed. By developing an approach based on differential inequality techniques coupled with Lyapunov function method. A numerical example is given for illustration.
Key words: Dynamical systems / Time scales / Exponential stability / Almost-anti periodic solution / Inertial Neural Networks
© The Authors, published by EDP Sciences, 2022
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