The Effect of Electric Field on the Synchronization of Improved HR Neuron Model
MSF,or main stability function,is a method that uses Lyapunov exponent theory to deter-mine the stability of synchronization states in complex homogeneous networks.A negative MSF value indicates that the network can synchronize.In this paper,a two-variable HR model is proposed to de-scribe the synchronization behavior of neurons under the effect of an electric field by a simplified MSF method,with the neuron size and applied electric field as regulatory factors.The relationship among the main stability function MSF,the charge size and applied electric field is studied.The results show that the electric field has a rich effect on neural network synchronization.A strong constant electric field can promote network synchronization,while An alternating electric field can inhibit synchronization.In ad-dition,the radius of the neuron also affects network synchronization.Under a larger radius of the neu-ron,the neural network will be easier to synchronize.
HR modelneural networksynchronizationelectric field effectmain stability func-tion
万方数据
维普
