Exponential Optimal Synchronization of Chaotic Cryptosystems: Neural-Network-Based Approach

摘要: This paper presents a systematic design methodology for neural-network (NN) based secure communications in multiple time-delay chaotic (MTDC) systems with optimal H∞ performance and cryptography. First, we use the n-shift cipher key to original message of transmission encryption. The encrypted is re-encrypted by using synchronization. A robust model-based fuzzy control then presented address effects modeling errors between MTDC NN models. Next, delay-dependent exponential stability criterion derived terms Lyapunov's direct method guarantee that trajectories slave system can approach those master system. Subsequently, conditions this are reformulated into linear matrix inequalities (LMIs). According LMIs, controller synthesized stabilize systems. not only realize synchronization, but also achieve minimizing disturbance attenuation level. Furthermore, error recovered stated key.