Global synchronization of coupled reaction–diffusion neural networks with general couplings via an iterative approach

2020 ◽  
Vol 85 (4) ◽  
pp. 635-669
Author(s):  
Jui-Pin Tseng

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.

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Wenjiao Sun ◽  
Guojian Ren ◽  
Yongguang Yu ◽  
Xudong Hai

This paper investigated the global synchronization of fractional-order memristive neural networks (FMNNs). To deal with the effect of reaction-diffusion and time delay, fractional partial and comparison theorem are introduced. Based on the set value mapping theory and Filippov solution, the activation function is extended to discontinuous case. Adaptive controllers with a compensator are designed owing to the existence of unknown parameters, with the help of Gronwall–Bellman inequality. Numerical simulation examples demonstrate the availability of the theoretical results.


2019 ◽  
Vol 341 ◽  
pp. 26-40 ◽  
Author(s):  
Zhen Qin ◽  
Jin-Liang Wang ◽  
Qing Wang ◽  
Lin-Jing Dai ◽  
Xiang-Yu Guo

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