A Novel Discrete Memristive Chaotic Rulkov Neuron Model with Electromagnetic Radiation and its Application in Image Encryption

Discrete memristor can simulate the electromagnetic induction effect of discrete neuron, which is important for neurological research. In this paper, a discrete memristor with cosine memristance is constructed firstly, then a memristive chaotic Rulkov (MC-Rolkov) neuron model with electromagnetic radiation effect is proposed. The complex dynamics is numerically studied by bifurcation diagrams, Lyapunov exponential (LE) spectrum and phase diagrams. The MC-Rolkov neuron model can generate self-growing chaotic attractors with sophisticated topological structures. Meanwhile, extreme multistability and transient chaotic attractors are found under some system parameters. Especially, the proposed MC-Rolkov neuron model can generate complex chaotic bursting behaviors. Finally, based on the MC-Rolkov neuron model, a new image encryption scheme is proposed, and the simulation results show that the proposed algorithm has excellent security characteristics.