Graph-Theoretic Approach to Finite-Time Synchronization for Fuzzy Cohen–Grossberg Neural Networks with Mixed Delays and Discontinuous Activations

2020 ◽  
Vol 52 (1) ◽  
pp. 905-933 ◽  
Author(s):  
Dongsheng Xu ◽  
Chengqiang Xu ◽  
Ming Liu
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Mixed Delays ◽  
Theoretic Approach ◽  
Graph Theoretic ◽  
Graph Theoretic Approach ◽  
Discontinuous Activations

scholarly journals Finite-time synchronization problem of a class of discontinuous Cohen–Grossberg neural networks with mixed delays via new switching design

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Zhaohong Xiang ◽  
Runjie Li
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Sufficient Conditions ◽  
Mixed Delays ◽  
Control Approach ◽  
Synchronization Problem ◽  
Analysis Theory ◽  
Discontinuous Activations ◽  
Discontinuous Activation Functions

AbstractThis paper investigates a class of generalized Cohen–Grossberg neural networks (CGNNs) with discontinuous activations and mixed delays. Based on the nonsmooth analysis theory, the drive-response concept, differential inclusions theory, we give several basic assumptions to gain the finite-time synchronization issue of CGNNs. Sufficient conditions are provided without the boundedness or monotonicity of discontinuous activation functions. Moreover, one can estimate the settling time’s upper bounds of the system. At last, two numerical examples and their simulations are given to further show the benefits of the obtained control approach.

Finite-Time Synchronization of Complex-Valued Neural Networks with Mixed Delays and Uncertain Perturbations

2017 ◽  
Vol 46 (1) ◽  
pp. 271-291 ◽  
Author(s):  
Chao Zhou ◽  
Wanli Zhang ◽  
Xinsong Yang ◽  
Chen Xu ◽  
Jianwen Feng
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Mixed Delays ◽  
Complex Valued
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