Finite-time synchronization for a class of fuzzy cellular neural networks with time-varying coefficients and proportional delays

2018 ◽  
Vol 338 ◽  
pp. 40-49 ◽  
Author(s):  
Wentao Wang
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks ◽  
Varying Coefficients ◽  
Proportional Delays ◽  
Time Varying Coefficients

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.

EXPONENTIAL CONVERGENCE BEHAVIOR OF FUZZY CELLULAR NEURAL NETWORKS WITH DISTRIBUTED DELAYS AND TIME-VARYING COEFFICIENTS

2009 ◽  
Vol 19 (07) ◽  
pp. 2455-2462 ◽  
Author(s):  
MAN-CHUN TAN
Keyword(s):  
Neural Networks ◽  
Sufficient Conditions ◽  
Cellular Neural Networks ◽  
Distributed Delays ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks ◽  
Lipschitz Continuous ◽  
Varying Coefficients ◽  
All Solutions ◽  
Time Varying Coefficients

In this paper, a class of fuzzy cellular neural networks (FCNNs) with distributed delays and time-varying coefficients is studied. By employing the mathematical analysis method, some sufficient conditions are derived for ensuring that all solutions of such FCNNs converge exponentially to zero. Both the Lipschitz continuous condition on activation functions and the differentiability of time-varying delays are not required in this study.

Finite-time synchronization for fuzzy inertial cellular neural networks with time-varying delays via integral inequality

2021 ◽  
pp. 1-14
Author(s):  
Zhenjie Wang ◽  
Wenxia Cui ◽  
Wenbin Jin
Keyword(s):  
Neural Networks ◽  
Integral Inequality ◽  
Finite Time ◽  
Time Synchronization ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Time Stability ◽  
Finite Time Stability ◽  
Synchronization Problem ◽  
Inequality Techniques

This paper mainly considers the finite-time synchronization problem of fuzzy inertial cellular neural networks (FICNNs) with time-varying delays. By constructing the suitable Lyapunov functional, and using integral inequality techniques, several sufficient criteria have been proposed to ensure the finite-time synchronization for the addressed (FICNNs). Without applying the known finite-time stability theorem, which is widely used to solve the finite-time synchronization problems for (FICNNs). In this paper, the proposed method is relatively convenient to solve finite-time synchronization problem of the addressed system, this paper extends the research works on the finite-time synchronization of (FICNNs). Finally, numerical simulations illustrated verify the effectiveness of the proposed results.

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