Synchronization Research And Application Of Coupled ML Neurons Model

Neuron is the most important functional unit of the nervous system, and the information transfer between neurons plays an important role in the normal operation of the nervous system. When neurons are stimulated, they will present a variety of discharge patterns. There contains abundant nonlinear dynamic behavior in the discharge and information coding process.This thesis researches the changes of ML neuronal firing rhythm when single parameter changes based on the improved ML neuron model through model simulation, the interspike interval bifurcation diagram, time response diagram and phase plane diagram. At the same time, this thesis considers the effects of the addition of DC electric field for the system, and discusses the periodic or chaotic discharge activities of the system when adding different intensities of DC electric field.This thesis establishes electrical synaptic coupled and chemical synaptic coupled ML neuron model, and studies the basic phenomenon of coupled neurons, and observes the firing activity and changes of system synchronization, and analyzes the influence of coupled neurons system when the existence of time delay, noise and both. It is researched that appropriate time delay and noise can promote the synchronization behavior for the non-synchronous electrical synapse coupling ML neuron system. It is also found that appropriate Gauss white noise can induce the synchronization behavior for the chemical synaptic coupling, and appropriate time-delay can eliminate the synchronization for chemical coupling, which has certain practical significance and provides theory basis for medical study of diseases caused by eliminating the synchronization.Finally, this thesis creates the system with adaptive control synchronization model which is based on the Lyapunov stability theorem. This system can dynamically adjust the controller values according to the initial values of the neuron model, and make the two coupled ML neuron systems in better synchronous state, which has good stability and adaptability. The controller is applied to chaotic secure communication in this thesis, and shows the well experimental result which has certain significance.