Global finite-time stability of delayed quaternion-valued neural networks based on a class of extended Lyapunov–Razumikhin methods
Li C. Cao J. Kashkynbayev A.
June 2023Springer Science and Business Media B.V.
Cognitive Neurodynamics
2023#17Issue 3729 - 739 pp.
In this paper, a class of global finite-time stability problem for quaternion-valued neural networks with time-varying delays are investigated by adopting an extended modification Lyapunov–Razumikhin (L–R) method and a new upper bounds estimation of system solution in terms of convergence rate was obtained. Firstly, a new extended method of L–R is proposed to solve the general difficulty to find a proper Lyapunov functional. Then, a new suitable controller is designed, the new conditions of inequalities global finite-time stability are obtained via combining with the former proposed L–R method in the separated real-valued system. Finally, for purpose of verifying the availability of the theorem presented, two given illustrative examples are shown.
Global finite-time , Modified L–R method , Quaternion , Stability , Time varying delays
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School of Mathematics, Southeast University, Nanjing, 210096, China
Research Center for Complex Systems and Network Sciences, and School of Mathematics, Southeast University, Nanjing, 210096, China
Department of Mathematics, Nazarbayev University, Kabanbay Batyr Avenue 53, Nur-Sultan, 010000, Kazakhstan
Yonsei Frontier Lab, Yonsei University, Seoul, 03722, South Korea
School of Mathematics
Research Center for Complex Systems and Network Sciences
Department of Mathematics
Yonsei Frontier Lab
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