Dynamical Analysis of Fuzzy Cellular Neural Networks with Time-varying Delays

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
Qianhong Zhang ◽  
Lihui Yang ◽  
Daixi Liao
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Dynamical Analysis ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks

scholarly journals Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays

2011 ◽  
Vol 21 (4) ◽  
pp. 649-658 ◽  
Author(s):  
Qianhong Zhang ◽  
Lihui Yang ◽  
Daixi Liao
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Exponential Stability ◽  
Differential Inequality ◽  
Sufficient Conditions ◽  
Coincidence Degree ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks ◽  
Inequality Technique

Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays Fuzzy cellular neural networks with time-varying delays are considered. Some sufficient conditions for the existence and exponential stability of periodic solutions are obtained by using the continuation theorem based on the coincidence degree and the differential inequality technique. The sufficient conditions are easy to use in pattern recognition and automatic control. Finally, an example is given to show the feasibility and effectiveness of our methods.

General Decay Synchronization for Fuzzy Cellular Neural Networks with Time-Varying Delays

2019 ◽  
Vol 20 (5) ◽  
pp. 551-560 ◽  
Author(s):  
Ahmadjan Muhammadhaji ◽  
Abdujelil Abdurahman
Keyword(s):  
Neural Networks ◽  
Numerical Simulations ◽  
Cellular Neural Networks ◽  
General Decay ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks ◽  
Activation Functions ◽  
General Activation ◽  
Inequality Techniques ◽  
Theoretical Results

AbstractThis paper studies the general decay synchronization (GDS) of a class of fuzzy cellular neural networks (FCNNs) with general activation functions and time-varying delays. By introducing suitable Lyapunov-Krasovskii functionals and employing useful inequality techniques, some novel criteria ensuring the GDS of considered FCNNs are established via a type of nonlinear control. In addition, two examples with numerical simulations are presented to illustrate the obtained theoretical results.

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.

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