Event-Triggered Impulsive Controller Design for Synchronization of Delayed Chaotic Neural Networks and Its Fractal Reconstruction: An Application to Image Encryption

This paper examines synchronization of delayed chaotic neural networks with impulsive control, event-triggered impulsive control, and event-triggered delayed impulsive control. Lyapunov-based event-triggered mechanism is constructed to derive few sufficient condi-tions in terms of Linear Matrix Inequalities (LMIs). The feedback and event-triggered gain matrices are evaluated with the help of numerical packages. The fractal interpolation func-tions are employed to reconstruct the chaotic sequence of the neural networks since the chaotic attractor has self-similar properties and coincides with the fractal functions. In this study, a linear fractal interpolation is used to reconstruct both the master-slave chaotic at -tractor and the encrypted chaotic attractor, with optimized scaling factors.Finally, an application of the image encryption algorithm is given in terms of RSA public -key cryptosystems, permutation, and finite field diffusion for the chaotic sequence gener-ated by fractal interpolation functions.(c) 2022 Elsevier Inc. All rights reserved.