Research On Scale-free Network Robustness And Network Delay Synchronization

In reality,there are all kinds of systems,large and small,which are connected by interaction to form a more complex and huge system.Complex network theory is an effective method to study complex system.In these years,the science and technology develop at high speed,the research of complicate network has drawed more attention than before.In a complex network,nodes and connections can be used to abstract the actual complex system.It is easy to comprehend the relevant properties of the network system by studying its structure and kinetics process.Therefore,the enthusiasm of complex network research in physics field has arisen at home and abroad.Network robustness and delay synchronization are both important research topics in complex network science.If the network is attacked,the nodes in the network have a certain probability of failure.In this paper,we propose a representation of fault network entropy,and study the different robustness of scale-free networks by using three strategies: random node removal,small degree node removal and large degree node removal.The network has different dynamic characteristics without and with time delay,In the case of time delay,the synchronization of dissipative coupled networks will be affected.In order to verify the synchronization stability of the dual constant time-delay network model,here established a dual constant time-delay network model with five nodes,Through the simulation,here analyzed verified the hypothesis of the synchronization model,and obtained the conclusion that the complex network determined by the model tends to be stable synchronization with time.In order to study the feasibility and effectiveness of adaptive feedback synchronization,here established a multi node global coupling network model with time delay.The simulation results show that the solution of delay differential equation and error vector of the model achieve stable synchronization state,and the adaptive feedback synchronization is feasible and effective.