Community structure of complex networks based on continuous neural network

2017 2nd International Seminar on Advances in Materials Science and Engineering

Dai, Ting-Ting^1 ; Shan, Chang-Ji^2 ; Dong, Yan-Shou^1

School of Mathematics and Statistics, Zhaotong University, Yunnan

657000, China^1

School of Physics and Electronic Information Engineering, Zhaotong University, Yunnan

657000, China^2

关键词: Community structures;    Continuous neural networks;    Eigen-value;    Key structures;    Network modularity;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/231/1/012154/pdf
DOI  :  10.1088/1757-899X/231/1/012154

来源: IOP

【 摘 要 】

As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.