Global Asymptotic Stabilization of Cellular Neural Networks with Proportional Delay via Impulsive Control

2019 ◽  
Vol 50 (2) ◽  
pp. 1969-1992 ◽  
Author(s):  
Kaizhong Guan ◽  
Junhao Yang
Keyword(s):  
Neural Networks ◽  
Impulsive Control ◽  
Cellular Neural Networks ◽  
Proportional Delay ◽  
Asymptotic Stabilization ◽  
Global Asymptotic Stabilization

Impulsive Control for a Class of Cellular Neural Networks with Proportional Delay

2018 ◽  
Vol 48 (3) ◽  
pp. 1459-1479 ◽  
Author(s):  
Kaizhong Guan ◽  
Qisheng Wang
Keyword(s):  
Neural Networks ◽  
Impulsive Control ◽  
Cellular Neural Networks ◽  
Proportional Delay

scholarly journals New convergence results on cellular neural networks with leakage delay and proportional delay

AIP Advances ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 075022
Author(s):  
Changjin Xu ◽  
Maoxin Liao ◽  
Peiluan Li
Keyword(s):  
Neural Networks ◽  
Cellular Neural Networks ◽  
Leakage Delay ◽  
Proportional Delay ◽  
Convergence Results

scholarly journals Almost Periodic Synchronization of Fuzzy Cellular Neural Networks with Time–Varying Delays via State–Feedback and Impulsive Control

2019 ◽  
Vol 29 (2) ◽  
pp. 337-349 ◽  
Author(s):  
Yongkun Li ◽  
Huimei Wang ◽  
Xiaofang Meng
Keyword(s):  
Neural Networks ◽  
State Feedback ◽  
Impulsive Control ◽  
Cellular Neural Networks ◽  
Banach Fixed Point Theorem ◽  
Time Varying ◽  
Fuzzy Cellular Neural Networks ◽  
Almost Periodic ◽  
Response Systems ◽  
Linear Differential

Abstract In this paper, we are concerned with drive-response synchronization for a class of fuzzy cellular neural networks with time varying delays. Based on the exponential dichotomy of linear differential equations, the Banach fixed point theorem and the differential inequality technique, we obtain the existence of almost periodic solutions of this class of networks. Then, we design a state feedback and an impulsive controller, and construct a suitable Lyapunov function to study the problem of global exponential almost periodic synchronization for the drive-response systems considered. At the end of the paper, we provide an example to verify the effectiveness of the theoretical results.

Impulsive control on global exponential stability for cellular neural networks with supremums

2012 ◽  
Vol 19 (4) ◽  
pp. 483-490 ◽  
Author(s):  
Ivanka M Stamova ◽  
Trayan Stamov ◽  
Neli Simeonova
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Global Exponential Stability ◽  
Impulsive Control ◽  
Cellular Neural Networks

scholarly journals Synchronizations of fuzzy cellular neural networks with proportional time-delay

2021 ◽  
Vol 6 (10) ◽  
pp. 10620-10641
Author(s):  
Ankit Kumar ◽  
◽  
Subir Das ◽  
Vijay K. Yadav ◽  
Rajeev ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Synchronization ◽  
Network Models ◽  
Lyapunov Stability Theory ◽  
Fixed Time ◽  
Cellular Neural Networks ◽  
Proportional Delay ◽  
Fuzzy Cellular Neural Networks ◽  
Neural Network Models ◽  
Theoretical Results

<abstract><p>In this article, finite-time and fixed-time synchronizations (FFTS) of fuzzy cellular neural networks (FCNNs) with interaction and proportional delay terms have been investigated. The synchronizations of FCNNs are achieved with the help of <italic>p</italic>-norm based on the inequalities defined in Lemmas 2.1 and 2.2. The analysis of the method with some useful criteria is also used during the study of FFTS. Under the Lyapunov stability theory, FFTS of fuzzy-based CNNs with interaction and proportional delay terms can be achieved using controllers. Moreover, the upper bound of the settling time of FFTS is obtained. In view of settling points, the theoretical results on the considered neural network models of this article are more general as compared to the fixed time synchronization (FTS). The effectiveness and reliability of the theoretical results are shown through two numerical examples for different particular cases.</p></abstract>

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