scholarly journals The Fast Fixed-Time Bipartite Synchronization of Coupled Delayed Neural Networks with Signed Graphs

2021 ◽  
Author(s):  
Shiju Yang ◽  
Chuandong Li ◽  
Yu Li ◽  
Ting Yang ◽  
Bo Li
Keyword(s):  
Neural Networks ◽  
Time Synchronization ◽  
Lyapunov Stability Theory ◽  
Fixed Time ◽  
Initial Condition ◽  
Signed Graphs ◽  
Comparison System ◽  
Delayed Neural Networks ◽  
Synchronization Problem ◽  
System Method

Abstract In this paper, the fixed-time bipartite synchronization problem for coupled delayed neural networks with signed graphs is discussed. Different from traditional neural networks, the interactions between nodes of delayed neural networks can be either collaborative or antagonistic. Furthermore, compared with the initial-condition based finite-time synchronization, the settling time is bounded by a constant within fixedtime regardless of the initial condition. It is worth noting that the fixed-time stable network for bipartite synchronization in this paper achieves more faster convergence than most existing publications. By applying constructing comparison system method, Lyapunov stability theory and inequality techniques, some sufficient criteria for fixed-time bipartite synchronization are obtained. Finally, two numerical examples are granted to display the performance of the obtained results.

scholarly journals Fixed-Time Synchronization Control of Delayed Dynamical Complex Networks

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1610
Author(s):  
Mei Liu ◽  
Binglong Lu ◽  
Zhanfeng Li ◽  
Haijun Jiang ◽  
Cheng Hu
Keyword(s):  
Complex Networks ◽  
Control Parameter ◽  
Time Synchronization ◽  
Adaptive Controller ◽  
Fixed Time ◽  
Synchronization Control ◽  
Delayed Neural Networks ◽  
Synchronization Problem ◽  
Delayed Dynamical Networks ◽  
Dynamical Complex Networks

Fixed-time synchronization problem for delayed dynamical complex networks is explored in this paper. Compared with some correspondingly existed results, a few new results are obtained to guarantee fixed-time synchronization of delayed dynamical networks model. Moreover, by designing adaptive controller and discontinuous feedback controller, fixed-time synchronization can be realized through regulating the main control parameter. Additionally, a new theorem for fixed-time synchronization is used to reduce the conservatism of the existing work in terms of conditions and the estimate of synchronization time. In particular, we obtain some fixed-time synchronization criteria for a type of coupled delayed neural networks. Finally, the analysis and comparison of the proposed controllers are given to demonstrate the validness of the derived results from one numerical example.

scholarly journals Predefined-Time Stability/Synchronization of Coupled Memristive Neural Networks With Multi-Links and Application in Secure Communication

2021 ◽  
Vol 15 ◽  
Author(s):  
Hui Zhao ◽  
Aidi Liu ◽  
Qingjié Wang ◽  
Mingwen Zheng ◽  
Chuan Chen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Secure Communication ◽  
Time Synchronization ◽  
Fixed Time ◽  
Settling Time ◽  
Memristive Neural Networks ◽  
Time Stability ◽  
Synchronization Problem ◽  
Communication Scheme ◽  
The Given

This paper explores the realization of a predefined-time synchronization problem for coupled memristive neural networks with multi-links (MCMNN) via nonlinear control. Several effective conditions are obtained to achieve the predefined-time synchronization of MCMNN based on the controller and Lyapunov function. Moreover, the settling time can be tunable based on a parameter designed by the controller, which is more flexible than fixed-time synchronization. Then based on the predefined-time stability criterion and the tunable settling time, we propose a secure communication scheme. This scheme can determine security of communication in the aspect of encrypting the plaintext signal with the participation of multi-links topology and coupled form. Meanwhile, the plaintext signals can be recovered well according to the given new predefined-time stability theorem. Finally, numerical simulations are given to verify the effectiveness of the obtained theoretical results and the feasibility of the secure communication scheme.

scholarly journals Finite-/fixed-time synchronization of delayed Clifford-valued recurrent neural networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
N. Boonsatit ◽  
G. Rajchakit ◽  
R. Sriraman ◽  
C. P. Lim ◽  
P. Agarwal
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Time Synchronization ◽  
Fixed Time ◽  
Computational Techniques ◽  
Feedback Controllers ◽  
System Models ◽  
Response System ◽  
Synchronization Problem ◽  
Error System

AbstractThis paper investigates the problem of finite-/fixed-time synchronization for Clifford-valued recurrent neural networks with time-varying delays. The considered Clifford-valued drive and response system models are firstly decomposed into real-valued drive and response system models in order to overcome the difficulty of the noncommutativity of the multiplication of Clifford numbers. Then, suitable time-delayed feedback controllers are devised to investigate the synchronization problem in finite-/fixed-time of error system. On the basis of new Lyapunov–Krasovskii functional and new computational techniques, finite-/fixed-time synchronization criteria are formulated for the corresponding real-valued drive and response system models. Two numerical examples demonstrate the effectiveness of the theoretical results.

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>

scholarly journals Robust Fixed-Time Synchronization for Coupled Delayed Neural Networks with Discontinuous Activations Subject to a Quadratic Polynomial Growth

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Lina Yu ◽  
Yunfei Ma ◽  
Yuntong Yang ◽  
Jingchao Zhang ◽  
Chunwei Wang
Keyword(s):  
Neural Networks ◽  
Time Synchronization ◽  
Fixed Time ◽  
Functional Method ◽  
Quadratic Polynomial ◽  
Linear Matrix ◽  
Delayed Neural Networks ◽  
Analysis Technique ◽  
Discontinuous Activations ◽  
Discontinuous Activation Functions

In this paper, we focus on the robust fixed-time synchronization for discontinuous neural networks (NNs) with delays and hybrid couplings under uncertain disturbances, where the growth of discontinuous activation functions is governed by a quadratic polynomial. New state-feedback controllers, which include integral terms and discontinuous factors, are designed. By Lyapunov–Krasovskii functional method and inequality analysis technique, some sufficient criteria, which ensue that networks can realize the robust fixed-time synchronization, are addressed in terms of linear matrix inequalities (LMIs). Moreover, the upper bound of the settling time, which is independent on the initial values, can be determined to any desired values in advance by the configuration of parameters in the proposed control law. Finally, two examples are provided to illustrate the validity of the theoretical results.

scholarly journals Fixed-Time Synchronization of Delayed Memristive Neural Networks with Discontinuous Activations

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Hao Pu ◽  
Fengjun Li
Keyword(s):  
Neural Networks ◽  
Time Synchronization ◽  
Fixed Time ◽  
Power Exponent ◽  
Memristive Neural Networks ◽  
Synchronization Problem ◽  
Neuron Activation ◽  
Discontinuous Activations ◽  
Inclusion Theory ◽  
Theoretical Results

In this paper, the fixed-time synchronization problem for a class of memristive neural networks with discontinuous neuron activation functions and mixed time-varying delays is investigated. With the help of the fixed-time stability theory, under the framework of Filippov solution and differential inclusion theory, several new and useful sufficient criteria for fixed-time synchronization are obtained by designing two types of energy-saving and simple controllers for the considered systems. Compared with the traditional fixed-time synchronization controller, the controllers used in this paper only have one power exponent term, which is a function of the system state error rather than a constant. Moreover, some previous relevant works are especially improved. Finally, two numerical examples are given to show the correctness and the effectiveness of the obtained theoretical results.

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