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Title: Global synchronization of coupled reaction–diffusion neural networks with general couplings via an iterative approach
Authors: 曾睿彬
Tseng, Jui-Pin
Contributors: 應數系
Date: 2020-08
Issue Date: 2021-05-27 11:42:06 (UTC+8)
Abstract: We establish a framework to investigate the global synchronization of coupled reaction–diffusion neural networks with time delays. The coupled networks under consideration can incorporate both the internal delays in each individual network and the transmission delays across different networks. The coupling scheme for the coupled networks is rather general, and its performance is not adversely affected by the restrictions commonly imposed by existing relevant investigations. Based on the proposed iterative approach, the problem of global synchronization is transformed into that of solving the corresponding homogeneous linear system of algebraic equations. The synchronization criterion is subsequently derived and can be verified with simple computations. Three numerical examples are presented to illustrate the effectiveness of the synchronization theory presented in this paper.
Relation: IMA Journal of Applied Mathematics, Vol.85, No.4, pp.635 - 669
Data Type: article
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