Global Robust Exponential Synchronization of Interval BAM Neural Networks with Multiple Time-Varying Delays

In this paper, we studied the problem of global robust exponential synchronization of interval bidirectional associative memory (BAM) neural networks with multiple time-varying delays. A direct method based on system solutions is proposed to give sufficient conditions for the global robust exponential synchronization of interval BAM neural networks under consideration. This method not only avoids the difficult to set up appropriate Lyapunov–Krasovskii functional, but also derives simpler global robust exponential synchronization criteria. To validate our results, we present two numerical examples that demonstrate the effectiveness of the obtained results. Furthermore, we use the global exponential synchronization criterion obtained to encrypt and decrypt color images, demonstrating the practical application of our research results.