Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks Via Hybrid Control

2021 ◽  
pp. 1-10
Author(s):  
Tianhu Yu ◽  
Jinde Cao ◽  
Leszek Rutkowski ◽  
Yi-Ping Luo
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Hybrid Control ◽  
Complex Valued

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

Finite-time synchronization of complex-valued neural networks with finite-time distributed delays

2020 ◽  
Vol 416 ◽  
pp. 152-157 ◽  
Author(s):  
Yanjun Liu ◽  
Junjian Huang ◽  
Yu Qin ◽  
Xinbo Yang
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Distributed Delays ◽  
Complex Valued

scholarly journals Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Ziye Zhang ◽  
Xiaoping Liu ◽  
Chong Lin ◽  
Bing Chen
Keyword(s):  
Neural Networks ◽  
Lyapunov Function ◽  
Recurrent Neural Networks ◽  
Finite Time ◽  
Time Delays ◽  
Time Synchronization ◽  
Great Difficulty ◽  
Activation Functions ◽  
Complex Valued ◽  
Independent Parameters

This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays. First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given. To achieve our aim, a nonlinear delayed controller with two independent parameters different from the existing ones is provided, which leads to great difficulty. To overcome it, a newly developed inequality is used. Then, via Lyapunov function approach, some criteria are derived to guarantee the finite-time synchronization of the considered system, and the settling time for synchronization is also estimated. Finally, two numerical simulations are given to support the effectiveness and advantages of the obtained results.

Finite-time synchronization of memristor-based complex-valued neural networks with time delays

2019 ◽  
Vol 383 (19) ◽  
pp. 2255-2263 ◽  
Author(s):  
Kaili Sun ◽  
Song Zhu ◽  
Yongchang Wei ◽  
Xiaoke Zhang ◽  
Fei Gao
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Delays ◽  
Time Synchronization ◽  
Complex Valued

Finite-time Synchronization of fractional-order complex-valued fuzzy cellular neural networks with time-varying delays

2021 ◽  
pp. 1-11
Author(s):  
Wenbin Jin ◽  
Wenxia Cui ◽  
Zhenjie Wang
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Finite Time ◽  
Time Synchronization ◽  
Sufficient Conditions ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Order Complex ◽  
Fuzzy Cellular Neural Networks ◽  
Complex Valued

Finite-time synchronization is concerned for the fractional-order complex-valued fuzzy cellular neural networks (FOCVFCNNs) with leakage delay and time-varying delays. Without using the usual complex-valued system decomposition method, this paper designs the different forms of the controllers by using 2-norm. And we construct the appropriate Lyapunov functional and apply inequality analytical techniques, some new sufficient conditions are obtained to ensure finite-time synchronization of the FOCVFCNNs. The upper bound of setting-time function is obtained. Finally, numerical examples are examined to illustrate the effectiveness of the analytical results.

Finite‐Time Synchronization of Complex‐Valued Delayed Neural Networks with Discontinuous Activations

2018 ◽  
Vol 20 (6) ◽  
pp. 2237-2247 ◽  
Author(s):  
Enli Wu ◽  
Xinsong Yang ◽  
Chen Xu ◽  
Fuad E. Alsaadi ◽  
Tasawar Hayat
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Delayed Neural Networks ◽  
Discontinuous Activations ◽  
Complex Valued
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