Global exponential stability conditions for quaternion-valued neural networks with leakage, transmission and distribution delays-Reference-Cited by-同舟云学术

Global exponential stability conditions for quaternion-valued neural networks with leakage, transmission and distribution delays

Published:2023 Issue:8 Volume:8 Page:19018-19038
ISSN:2473-6988
Container-title:AIMS Mathematics
language:
Short-container-title:MATH

Author:

Zhu Li¹,Cong Er-yong¹²,Zhang Xian³⁴

Affiliation:

1. Department of Mathematics, Harbin University, Harbin 150086, China

2. Heilongjiang Provincial Key Laboratory of the Intelligent Perception and Intelligent Software, Harbin University, Harbin 150080, China

3. School of Mathematical Science, Heilongjiang University, Harbin 150080, China

4. Heilongjiang Provincial Key Laboratory of the Theory and Computation of Complex Systems, Heilongjiang University, Harbin 150080, China

Abstract

<abstract><p>This paper studies the global exponential stability problem of quaternion-valued neural networks (QVNNs) with leakage, transmission, and distribution delays. To address this issue, a direct method based on system solutions is proposed to ensure the global exponential stability of the considered network models. In addition, this method does not need to construct any Lyapunov-Krasovskii functional, which greatly reduces the amount of computation. Finally, a numerical example is given to demonstrate the effectiveness of the proposed results.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

Reference44 articles.

1. Y. Chen, X. Zhang, Y. Xue, Global exponential synchronization of high-order quaternion Hopfield neural networks with unbounded distributed delays and time-varying discrete delays, Math. Comput. Simulat., 193 (2022), 173–189. http://doi.org/10.1016/j.matcom.2021.10.012

2. Z. Dong, X. Wang, X. Zhang, M. Hu, T. N. Dinh, Global exponential synchronization of discrete-time high-order switched neural networks and its application to multi-channel audio encryption, Nonlinear Anal. Hybrid Syst., 47 (2023), 101291. http://doi.org/10.1016/j.nahs.2022.101291

3. J. Hu, Z. Wang, G.-P. Liu, H. Zhang, R. Navaratne, A prediction-based approach to distributed filtering with missing measurements and communication delays through sensor networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51 (2021), 7063–7074. http://doi.org/10.1109/TSMC.2020.2966977

4. J. Hu, G. Liu, H. Zhang, H. Liu, On state estimation for nonlinear dynamical networks with random sensor delays and coupling strength under event-based communication mechanism, Inform. Sciences, 511 (2020), 265–283. http://doi.org/10.1016/j.ins.2019.09.050

5. P. Yu, F. Deng, Almost sure stability of stochastic neutral Cohen-Grossberg neural networks with levy noise and time-varying delays, Asian J. Control, 25 (2023), 371–382. http://doi.org/10.1002/asjc.2777