Synchronous Analysis Of Network Model Under Delayed Impulse Control

In recent years,synchronization of complex networks based on time-delay impulsive control strategies has been widely applied in many fields,and has received great attention from a large number of experts and scholars,and there are lots of many excellent results.Delayed impulsive control strategies have the advantages of timeliness,simplicity,low energy consumption,and discontinuity.This plays a very important role in studying the synchronization of complex network models.This thesis mainly discusses the synchronization of neural networks and complex networks based on time-delay impulsive control strategies.In this thesis,the synchronization problem of several types of complex networks is discussed by introducing time-delay impulsive controllers.The main contents include:(1)The synchronization of drive-response neural networks with time-delay is studied.A new impulsive delay inequality is proposed,and a synchronization criterion for a drive-response neural network is established based on a distributed delay impulsive strategy.(2)The quantization synchronization of drive-response neural networks with time delays on the time scale is studied.A new quantized impulsive delay inequality based on time scales is proposed,and an estimate of the solution of the inequality is obtained.The obtained results reveal the relationship between synchronization criteria and quantized impulsive.(3)The quantization synchronization of complex networks on time scales is studied.This paper proposes a synchronization method and delay grouping strategy for complex networks on time scales using impulsive quantization control and delayed impulsive control.By controlling delay partitioned subgroup nodes with impulsive quantization,synchronization of complex networks on time scales can be achieved.