Chaos Synchronization And Control Of Ghostburster Neuron

The nerve system is basically composed of neurons, the generation and proposition between the neurons indicate abundant nonlinear characteristic. The research of recent years shows that different models have their own bursting under the external stimulation, such as periodical spikes, chaotic and synchronized firing. The perturbation of stimulation may result in the change of neuronal state, so the research on the nonlinear characteristic and dynamical control of the nerve cell is of great significant.In this paper, take the Ghostburster neuron as study object and describe the dynamic characteristic on the both soma and dendrite. First use the applied current as stimulation, analyze its dynamical characteristic and find the Largest Lyapunov exponent spectra to approve the chaos. The unidirectional-coupled two-neurons model is established to study chaos synchronization of the action potentials between neurons in external electric field. A H-infinity variable universe adaptive fuzzy synchronization control, active synchronization control and adaptive synchronization control based on RBF neural network are designed to control and synchronize two coupled Ghostburster neurons. The theoretical analysis and the numerical simulations show the effectiveness of these proposed methods.The result can throw light on the researches of the quantitative analysis of the acupuncture and functional stimulation of the nerve system.