Dynamics Analysis of Fractional-Order Memristive Neural Network and Its Application in Military Image Encryption

The chaotic signals generated by the memristive neuron system provide high security, which is important for image encryption. In this paper, a fractional-order memristive neuron network system is proposed. The system has a symmetric coexistence behavior through numerical simulations. Moreover, including an external current in this neuronal network model can generate bursting behavior. Due to the high security of chaotic sequences generated by the neuronal network system. A new military image encryption scheme is proposed using fractional order memristive neuron system and hash function. The results are analyzed through security tests, which show that the proposed encryption scheme provides excellent security performance for military image communication.