Global exponential synchronization of competitive neural networks with D operators and mixed delays and an application to secure communication

The global exponential synchronization (GES) of competitive neural networks (CNNs) with mixed delays and D operators is the main topic of this research. To ensure GES between the drive and response CNNs, effective controllers are designed in this paper. Based on this, we propose a direct analysis approach based on system solutions, which not only eliminates the need to construct the Lyapunov–Krasovskii functional but also simplifies the process of solving the synchronization criteria and reduces the workload and computational complexity to a large extent. Additionally, it is discussed how the proposed synchronization method is applied to secure communication. Eventually, numerical examples and an application example will confirm the theoretical and practical usefulness of the approach. It is important to note that this research is the first to investigate the GES issue for CNNs with D operators and mixed delays.