Novel Synchronization Conditions for the Unified System of Multi-Dimension-Valued Neural Networks

Jianying Xiao () and Yongtao Li
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Jianying Xiao: School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu 610106, China
Yongtao Li: College of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610050, China

Mathematics, 2022, vol. 10, issue 17, 1-24

Abstract: This paper discusses the novel synchronization conditions about the unified system of multi-dimension-valued neural networks (USOMDVNN). First of all, the general model of USOMDVNN is successfully set up, mainly on the basis of multidimensional algebra, Kirchhoff current law, and neuronal property. Then, the concise Lyapunov–Krasovskii functional (LKF) and switching controllers are constructed for the USOMDVNN. Moreover, the new inequalities, whose variables, together with some parameters, are employed in a concise and unified form whose variables can be translated into special ones, such as real, complex, and quaternion. It is worth mentioning that the useful parameters really make some contributions to the construction of the concise LKF, the design of the general controllers, and the acquisition of flexible criteria. Further, we acquire the newer criteria mainly by employing Lyapunov analysis, constructing new LKF, applying two unified inequalities, and designing nonlinear controllers. Particularly, the value of the fixed time is less than the other ones in some existing results, owing to the adjustable parameters. Finally, three multidimensional simulations are presented, to demonstrate the availability and progress of the achieved acquisitions.

Keywords: multi-dimension-valued neural networks; quaternion-valued neural networks; complex-valued neural networks; synchronization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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