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This paper presents an approach for fixed‐time synchronization (FIXTS) of neural networks (NNs) by designing quantized intermittent controller. Under the intermittent controller, the synchronization between neural network systems with time delay can be realized. Based on intermittent strategy, FIXTs theory is proposed, and a sufficient condition is established to realize the FIXTS of the master–slave NNs. At the same time, the establishment time of FIXTS is estimated. Finally, the simulation of Gilli attractor to prove the validity of the proposed method. [ABSTRACT FROM AUTHOR]

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]

In this paper, we study the fixed-time synchronization (FIXTS) of neural networks (NNs) with parameter uncertainties via quantized intermittent control. Based on the intermittent control strategy and quantitative control theory, sufficient conditions are established to achieve synchronization of NNs and the synchronization time can be estimated. In addition, this paper also considers the synchronization of NNs under different situations. Finally, a simulation example is given to verify the correctness of the proposed theory. [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 considers the fixed-time synchronization (FIXTS) of neural networks (NNs) by using quantized intermittent control (QIC). Based on QIC, a fixed-time controller is designed to ensure that the NNs achieve synchronization in finite time. With this controller, the settling time can be estimated regardless of initial conditions. After ensuring that the system has stabilized through this strategy, it is suitable for image protection given the behavior of the system. Meanwhile, the encryption effect of the image depends on the encryption algorithm, and the quality of the decrypted image depends on the synchronization error of NNs. The numerical results show that the designed controller is effective and validate the practical application of FIXTS of NNs in image protection. [ABSTRACT FROM AUTHOR]