Node Inactivation Of Network Structure And Dynamics

The complex network can describe the structure of many systems in the real world. Thanks to the concepts and methods of statistical mechanics, in the past ten years in the study of complex networks has experienced rapid development. The related research now is divided into a number of areas, including problems of nonlinear dynamics on the network is a very important field. This paper focuses on the problems related to the network nodes. Delete nodes in complex networks, the structure attributes of the network will have a certain change. Study on changes of the structure we can make the network structure characteristics of more in-depth understanding and understanding. Study removed nodes after changes in the network dynamics can be so that we can have a more systematic understanding of global dynamics of the network. The main research 1 Study network subgraph features when a node is removed. In random network and BA scale-free network, with randomly removed nodes and attempted to remove the increase of the number of nodes calculated in addition to the number of the largest connected graph and other sub group. The results showed their characteristics with node deletion ratio of F increases from 0 to 1,the number of sub group increased first and then decreased. The number of sub group contains nodes number accounted for most of the total number of sub group. A smaller group, its size and the number of the corresponding approximate power-law relationship. Scale free network under attack, peak group number of smaller deletion probability appeared in and quickly disappeared.2 We study the growth of network, the number of nodes in the network with increased time of network. In the process of network growth, some nodes are no longer used is the loss of activity, such as citation network. Inactivation of an existing node network growth model to simulate the citation network in the article from now no more than a particular year, of which the number of active nodes fixed. We propose an improved model, which is to increase the number of active nodes. Consistent with this model and citation network in the older literature is less likely to be cited in new literature phenomenon, and traditional BA model and its phenomena do not meet. Improved model has the characteristics of more of the real system, but our study shows that with the original model can get some properties of the real system. The model generated by the network node degree distribution and cumulative distribution has a power-law properties. In addition, this model has the characteristics of high clustering coefficient. But the traditional BA model with the increase of the scale of the model, the clustering coefficient decreased gradually.3 The most important part is to study the influence of the dynamics of node deletion. In a complex system in different parts may perform different functions and mutual cooperation, such as the brain. Can realize the independent function using the modular network (separation) and collaboration (integration) balance. This paper studied the effect of deleting node for separation and integration. In the network module, we randomly delete some of the nodes, network module between the degree of integration and separation degree of change were studied. Our study shows that in a network of separation and integration of balance, delete nodes lead to the destruction of the balance, and strengthened by the integration. The actual phenomena of the results of the kinetic model and human aging changes under the same. The simulation results: after the change of the network module integration degree and degree of separation to reach equilibrium, we need to re adjust the strength of connection between the network module.