Supported by the National Natural Science Foundation of China under Grant No.60874080;the Commonweal Application Technique Research Project of Zhejiang Province under Grant No.2012C2316;the Open Project of State Key Lab of Industrial Control Technology of Zhejiang University under Grant No.ICT1107
We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in nongrowth random networks. In this model, we use multiple-edges to represent the connections between vertices and define...
In this paper,we study a long-range percolation model on the lattice Z d with multi-type vertices and directed edges.Each vertex x ∈ Z d is independently assigned a non-negative weight Wx and a type ψx,where(Wx) x∈...
Supported by National Natural Science Foundation of China under Grant Nos. 60504027 and 60874080;the Open Project of State Key Lab of Industrial Control Technology under Grant No. ICT1107
We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique (maximal complete sub-graph) at. each time step. And the cliques in the network overlap with each othe...
Supported by "Qing Lan" Talent Engineering Funds by Lanzhou Jiaotong University under Grant No. QL-08-18A
We investigate the influence of blurred ways on pattern recognition of a Barabasi-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of infor...
National Natural Science Foundation of China under Grant Nos.60504019 and 70431002
In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned i...
The project supported by National Natural Science Foundations of China under Grant Nos and Technology Foundation of Beijing Jiaotong University under Grant No. 2004SM026 70471088 and 70225005 and Che Science.
In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment...