Secure communication based on chaos synchronization using brain emotional learning

Abstract

This paper presents a secure communication system based on chaos synchronization using brain emotional learning-based intelligent controller (BELBIC). Uncertainties, including parametric uncertainties and external disturbances are approximated using emotional learning. The obtained estimation is used in the controller or observer to apply appropriate input to the receiver to synchronize the chaotic signals of transmitter and receiver. The proposed system can effectively reduce the synchronization error. In comparison with other intelligent systems such as neuro-fuzzy systems, brain emotional learning has a more straightforward structure and consequently its tuning is simpler. Stability analysis using Lyapunov direct method guarantees that internal signals are bounded and the synchronization error converges to zero. Moreover, for secure communication and cryptography, an observer using emotional learning is developed. Simulation results verify the satisfactory performance of the proposed synchronization controller and observer.