Fixed-Time Synchronization of Neural Networks Based on Quantized Intermittent Control for Image Protection

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.

Automated summary

This paper discusses the use of QIC to achieve FIXTS of NNs and designs a fixed-time controller to ensure synchronization in finite time. After confirming system stability, it is suitable for image protection – the encryption effect and decryption quality depend on the encryption algorithm and NNs synchronization error.