<abstract xmlns="http://www.w3.org/1999/xhtml"><p>A class of Clifford-valued high-order Hopfield neural networks (HHNNs) with state-dependent and leakage delays is considered. First, by using a continuation theorem of coincidence degree theory and the Wirtinger inequality, we obtain the existence of anti-periodic solutions of the networks considered. Then, by using the proof by contradiction, we obtain the global exponential stability of the anti-periodic solutions. Finally, two numerical examples are given to illustrate the feasibility of our results.</p></abstract>

A class of Clifford-valued high-order Hopfield neural networks (HHNNs) with state-dependent and leakage delays is considered. First, by using a continuation theorem of coincidence degree theory and the Wirtinger inequality, we obtain the existence of anti-periodic solutions of the networks considered. Then, by using the proof by contradiction, we obtain the global exponential stability of the anti-periodic solutions. Finally, two numerical examples are given to illustrate the feasibility of our results.

Anti–Periodic Solutions for Clifford–Valued High–Order Hopfield Neural Networks with State–Dependent and Leakage Delays

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

A class of Clifford-valued high-order Hopfield neural networks (HHNNs) with state-dependent and leakage delays is considered. First, by using a continuation...

Anti–Periodic Solutions for Clifford–Valued High–Order Hopfield Neural Networks with State–Dependent and Leakage Delays

Online veröffentlicht: 03. Apr. 2020

Seitenbereich: 83 - 98

Eingereicht: 14. März 2019

Akzeptiert: 18. Okt. 2019

DOI: https://doi.org/10.34768/amcs-2020-0007

Schlüsselwörter
Clifford-valued high-order Hopfield neural network, anti-periodic solution, coincidence degree, time-varying delay

© 2020 Nina Huo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Anti–Periodic Solutions for Clifford–Valued High–Order Hopfield Neural Networks with State–Dependent and Leakage Delays

Online veröffentlicht: 03. Apr. 2020

Seitenbereich: 83 - 98

Eingereicht: 14. März 2019

Akzeptiert: 18. Okt. 2019

DOI: https://doi.org/10.34768/amcs-2020-0007

SchlüsselwörterClifford-valued high-order Hopfield neural network, anti-periodic solution, coincidence degree, time-varying delay

© 2020 Nina Huo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Clifford-valued high-order Hopfield neural network, anti-periodic solution, coincidence degree, time-varying delay