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In this paper, the bipartite synchronization of signed Lur'e network is studied under intermittent control, where the communication relationship of these adjacent nodes in the network can be either cooperative or competitive. Assuming that the network is structurally balanced, bipartite synchronization can be reached with some conditions and coordinate transform criterion. Then, Based on Lyapunov stability theory, some important norms are established. Ultimately, the simulation results can illustrate validness of theoretical analysis. • Based on the features of coordinate control, Lur'e networks is utilized to study synchronization problem. And synchronizing all nodes is the ultimate goal by adopting coordinate transform and nonlinear function. • Intermittent and pinning algorithm are used to achieve synchronization in signed Lur'e networks. Pinning control is a control strategy, which only needs to control finite nodes of the system [1]. Thus it is proposed to achieve bipartite leader-following synchronization in networks. • Finally, a numerical example is given to demonstrate the effectiveness and feasibility of the obtained results. [ABSTRACT FROM AUTHOR]

This paper studies the fixed-time synchronization (FDTS) of complex-valued neural networks (CVNNs) based on quantized intermittent control (QIC) and applies it to image protection and 3D point cloud information protection. A new controller was designed which achieved FDTS of the CVNNs, with the estimation of the convergence time not dependent on the initial state. Our approach divides the neural network into two real-valued systems and then combines the framework of the Lyapunov method to give criteria for FDTS. Applying synchronization to image protection, the image will be encrypted with a drive system sequence and decrypted with a response system sequence. The quality of image encryption and decryption depends on the synchronization error. Meanwhile, the depth image of the object is encrypted and then the 3D point cloud is reconstructed based on the decrypted depth image. This means that the 3D point cloud information is protected. Finally, simulation examples verify the efficacy of the controller and the synchronization criterion, giving results for applications in image protection and 3D point cloud information protection. [ABSTRACT FROM AUTHOR]

This paper is dedicated to addressing the issue of the finite-time synchronization of complexed-valued neural networks with finite-time distributed delays. Some results are derived for finite-time synchronization of the drive-response system using the new Lyapunov–Krasovskii function and the analysis techniques. We then propose several numerical examples to determine the effectiveness of the results. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a finite-time lag synchronization of coupled neural networks with time delay is investigated. By means of the Lyapunov stability theory, a feedback controller is designed for achieving lag synchronization between two delayed neural networks systems in finite time. Paper extends some basic results from the area of finite time to time-delay systems. Numerical simulations on coupled Lu neural systems illustrate the effectiveness of the results. [Copyright &y& Elsevier]

Abstract: This paper deals with the synchronization of two coupled identical chaotic systems with parameter mismatch via using periodically intermittent control. In general, parameter mismatches are considered to have a detrimental effect on the synchronization quality between coupled identical systems: in the case of small parameter mismatches the synchronization error does not decay to zero or even a nonzero mean. Larger values of parameter mismatches can even result in the loss of synchronization. via intermittent control with periodically intervals, we can obtain the weak synchronization. Some sufficient conditions for the stabilization and weak synchronization of a large class of coupled identical chaotic systems will be derived by using Lyapunov stability theory. The analytical results are confirmed by numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, the generalized synchronization of nonlinear chaotic systems is investigated. Based upon reversibility of the Jacobian matrix and matrix theory, we carry out a series of elementary column transformations to Jacobian matrix. And then, according to Lyapunov function theory, sufficient conditions for generalized synchronization between drive system and response system with different dimensions are obtained. Numerical simulations are also given to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time synchronization of complex networks (CNs) with nonidentical nodes and stochastic noise perturbations. By designing new controllers, constructing Lyapunov functions and using the properties of Weiner process, different synchronization criteria are derived according to whether the node systems in the CNs or the goal system satisfies the corresponding conditions. Moreover, the role of the designed controllers is analyzed in great detail by constructing a suitable comparison system and a new method is presented to estimate the settling time by utilizing the comparison system. Results of this paper can be applied to both directed and undirected weighted networks. Numerical simulations are offered to verify the effectiveness of our new results. [ABSTRACT FROM AUTHOR]

This paper focuses on the hybrid effects of coupling, time-varying delay, intermittent controller on memristor-based neural networks. Firstly, we constructed an array of linearly coupled memristor-based neural networks with time-varying delay. Secondly, our sufficient conditions, ensuring the stability and synchronization, are dependent on coupling and intermittent control and show coupling and intermittent control on the stability and synchronization of memristor-based neural networks. Finally, numerical simulations were given to verify the theoretical results. [ABSTRACT FROM AUTHOR]