A new approach for accuracy-preassigned finite-time exponential synchronization of neutral-type Cohen–Grossberg memristive neural networks involving multiple time-varying leakage delays

Er-Yong Cong; Yantao Wang; Xian Zhang; Li Zhu; Er-Yong Cong; Yantao Wang; Xian Zhang; Li Zhu

doi:10.3934/math.2025496

AIMS Mathematics

2025, Volume 10, Issue 5: 10917-10942. doi: 10.3934/math.2025496

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Research article

A new approach for accuracy-preassigned finite-time exponential synchronization of neutral-type Cohen–Grossberg memristive neural networks involving multiple time-varying leakage delays

1.
Department of Mathematics, Harbin University, Harbin 150086, China
2.
School of Mathematical Science, Heilongjiang University, Harbin 150080, China
3.
Heilongjiang Provincial Key Laboratory of the Theory and Computation of Complex Systems, Heilongjiang University, Harbin 150080, China
4.
Heilongjiang Provincial Key Laboratory of the Intelligent Perception and Intelligent Software, Harbin University, Harbin 150080, China

Received: 28 February 2025 Revised: 26 April 2025 Accepted: 30 April 2025 Published: 13 May 2025
MSC : 93D20

We studied the problem of accuracy-preassigned finite-time exponential synchronization of neutral-type Cohen–Grossberg memristive neural networks involving time-varying multiple leakage and transmission delays. First, a novel method was presented to give an estimation formula for solutions of the error system. Then, the estimation formula was used to establish sufficient conditions guaranteeing accuracy-preassigned finite-time exponential synchronization of the considered memristive Cohen–Grossberg neural networks. The obtained sufficient conditions were composed of some linear scalar inequalities that was easy to solve by employing standard tool softwares. Moreover, the approach proposed here was based on the concept of accuracy-preassigned finite-time exponential synchronization, and Lyapunov–Krasovskii functionals or model transformations were not involved, simplifying the theorematic proof. Finally, two numerical examples were given to present the validity of theorematic results.
Citation: Er-Yong Cong, Yantao Wang, Xian Zhang, Li Zhu. A new approach for accuracy-preassigned finite-time exponential synchronization of neutral-type Cohen–Grossberg memristive neural networks involving multiple time-varying leakage delays[J]. AIMS Mathematics, 2025, 10(5): 10917-10942. doi: 10.3934/math.2025496

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Abstract

We studied the problem of accuracy-preassigned finite-time exponential synchronization of neutral-type Cohen–Grossberg memristive neural networks involving time-varying multiple leakage and transmission delays. First, a novel method was presented to give an estimation formula for solutions of the error system. Then, the estimation formula was used to establish sufficient conditions guaranteeing accuracy-preassigned finite-time exponential synchronization of the considered memristive Cohen–Grossberg neural networks. The obtained sufficient conditions were composed of some linear scalar inequalities that was easy to solve by employing standard tool softwares. Moreover, the approach proposed here was based on the concept of accuracy-preassigned finite-time exponential synchronization, and Lyapunov–Krasovskii functionals or model transformations were not involved, simplifying the theorematic proof. Finally, two numerical examples were given to present the validity of theorematic results.

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