Chaos synchronization using adaptive quantum neural networks and its application in secure communication and cryptography

This paper proposes an adaptive controller for chaos synchronization using quantum neural networks (QNN). The main purpose is to design a communication system for transmission of information securely. In many applications of chaotic systems, the exact model of system is not available and may involve uncertainties such as external disturbance and parametric uncertainties originating from environmental conditions. To estimate the uncertainties in the receiver and improve the accuracy of synchronization and recovering the message signal for secure communication applications, a QNN is used. The parameters of the proposed system should be estimated by applying the adaptive rules obtained by Lyapunov theorem. Taylor series expansion has been utilized to obtain a linear relation between the output of quantum neural network and its adaptive parameters. Simulation results show that the synchronization procedure for state variables of the master and slave systems is performed well with negligible synchronization error. Also, its application is investigated in secure communication and cryptography.