scholarly journals Stability of Fractional Order Fuzzy Cellular Neural Networks with Distributed Delays via Hybrid Feedback Controllers

2021 ◽  
Vol 53 (2) ◽  
pp. 1469-1499
Author(s):  
Ajendra singh ◽  
Jitendra Nath Rai
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Cellular Neural Networks ◽  
Distributed Delays ◽  
Fuzzy Cellular Neural Networks ◽  
Feedback Controllers

scholarly journals Stability of fractional order fuzzy cellular neural networks with distributed delays via hybrid feedback controllers

2021 ◽  
Author(s):  
Ajendra Sing ◽  
Jitendra Nath Rai
Keyword(s):  
Neural Networks ◽  
Feedback Control ◽  
Fractional Order ◽  
Sufficient Conditions ◽  
Cellular Neural Networks ◽  
Control Technique ◽  
Fuzzy Cellular Neural Networks ◽  
Feedback Controllers ◽  
Lyapunov Approach ◽  
Analysis Techniques

Abstract This article studies the Global Mittag-Leffler stability of fractional order fuzzy cellular neural networks via hybrid feedback controllers. Based on hybrid feedback control technique Lyapunov approach, and some novel analysis techniques of fractional calculation, some sufficient conditions are obtained to guarantee the Global Mittag-lefflers stability. Finally, two simulation example are given to illustrate the effectiveness of the proposed method.

EXPONENTIAL STABILITY OF STOCHASTIC FUZZY CELLULAR NEURAL NETWORKS WITH DISTRIBUTED DELAYS

2009 ◽  
Vol 19 (10) ◽  
pp. 3387-3395 ◽  
Author(s):  
LIPING CHEN ◽  
RANCHAO WU
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Lyapunov Functional ◽  
Equilibrium Solution ◽  
Sufficient Conditions ◽  
Cellular Neural Networks ◽  
Distributed Delays ◽  
Fuzzy Cellular Neural Networks ◽  
Mean Square Exponential Stability ◽  
Inequality Techniques

The exponential stability of a class of stochastic fuzzy cellular neural networks with distributed delays is investigated in this paper. By using analytic methods such as Lyapunov functional, Itô's formula, inequality techniques and non-negative semimartingale convergence theorem, the sufficient conditions guaranteeing the almost sure and mean square exponential stability of its equilibrium solution are respectively obtained. For illustration, an example is given to show the feasibility of 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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