New criteria on event-triggered cluster synchronization of neutral-type neural networks with Lévy noise and non-Lipschitz condition

2020 ◽  
Vol 384 ◽  
pp. 156-169 ◽  
Author(s):  
Yuqing Sun ◽  
Yihong Zhang ◽  
Wuneng Zhou ◽  
Xin Zhang ◽  
Xiaofeng Wang
Keyword(s):  
Neural Networks ◽  
Lipschitz Condition ◽  
Neutral Type ◽  
Cluster Synchronization ◽  
Lévy Noise ◽  
Levy Noise ◽  
New Criteria ◽  
Event Triggered

Adaptive state estimation of Markov switched neural networks driven by Lévy noise

2019 ◽  
Vol 42 (2) ◽  
pp. 330-336
Author(s):  
Dongbing Tong ◽  
Qiaoyu Chen ◽  
Wuneng Zhou ◽  
Yuhua Xu
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Sufficient Conditions ◽  
Lyapunov Stability Theory ◽  
Lévy Noise ◽  
Linear Matrix ◽  
Delayed Neural Networks ◽  
Switched Neural Networks ◽  
Inequality Technique ◽  
Levy Noise

This paper proposes the [Formula: see text]-matrix method to achieve state estimation in Markov switched neural networks with Lévy noise, and the method is very distinct from the linear matrix inequality technique. Meanwhile, in light of the Lyapunov stability theory, some sufficient conditions of the exponential stability are derived for delayed neural networks, and the adaptive update law is obtained. An example verifies the condition of state estimation and confirms the effectiveness of results.

Synchronization of delayed neural networks with Lévy noise and Markovian switching via sampled data

2015 ◽  
Vol 81 (3) ◽  
pp. 1179-1189 ◽  
Author(s):  
Jun Yang ◽  
Wuneng Zhou ◽  
Peng Shi ◽  
Xueqing Yang ◽  
Xianghui Zhou ◽  
...  
Keyword(s):  
Neural Networks ◽  
Markovian Switching ◽  
Lévy Noise ◽  
Sampled Data ◽  
Delayed Neural Networks ◽  
Levy Noise
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