@article{Gao2022, 
author = {Jin Gao and Lihua Dai},
title = {Anti-periodic synchronization of quaternion-valued high-order Hopfield neural networks with delays},
year = {2022},
journal = {AIMS Mathematics},
volume = {7},
number = {8},
pages = {14051-14075},
keywords = {inertial neural networks, quaternion, anti-periodic solutions, non-reduced order method, synchronization},
url = {https://www.sciopen.com/article/10.3934/math.2022775},
doi = {10.3934/math.2022775},
abstract = {This paper proposes a class of quaternion-valued high-order Hopfield neural networks with delays. By using the non-decomposition method, non-reduced order method, analytical techniques in uniform convergence functions sequence, and constructing Lyapunov function, we obtain several sufficient conditions for the existence and global exponential synchronization of anti-periodic solutions for delayed quaternion-valued high-order Hopfield neural networks. Finally, an example and its numerical simulations are given to support the proposed approach. Our results play an important role in designing inertial neural networks.}
}