Synchronization of Chaotic System Using a Brain-Imitated Neural Network Controller and Its Applications for Secure Communications

This paper proposes a new hybrid algorithm for secure communication applications. The proposed includes fuzzy brain emotional learning controller (FBELC), recurrent cerebellar model articulation (RCMAC), and robust compensator (RC). main brain-imitated neural network is combination of the RCMAC FBELC, which mathematical that approximates decision activity human brain. A inference system also merged into FBELC to produce an efficient structure, then it used 3-dimensional (3D) Genesio chaotic audio image systems show potency performance algorithm. In first application, encryption enhance security information transmission, several standard images are applied synchronization communication. second signal embedded in 3D trajectory, as carrier signal, after using method decryption, source can be retrieved. comparisons simulation results analyses root mean square error recent algorithms performed validate efficiency point out our attain better performance, achieve more communications.