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Antiperiodic solutions to delayed inertial quaternion‐valued neural networks
Author(s) -
Xu Changjin,
Li Peiluan,
Liao Maoxin,
Liu Zixin,
Xiao Qimei
Publication year - 2020
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.6469
Subject(s) - quaternion , mathematics , artificial neural network , inertial frame of reference , lyapunov function , control theory (sociology) , exponential stability , computer science , classical mechanics , artificial intelligence , geometry , physics , control (management) , nonlinear system , quantum mechanics
This manuscript mainly deals with quaternion‐valued neural networks (QVNNs) with delays and inertial term. Using Wirtinger inequality and coincidence degree theory, a new sufficient criterion to ensure the existence of antiperiodic solution of involved quaternion‐valued neural networks is derived. With the aid of Lyapunov function, we discuss the exponential stability of antiperiodic solutions to quaternion‐valued neural networks. Numerical simulations are presented to illustrate the established theoretical findings.