xiang Li
Beijing University of Posts and Telecommunications
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Publication
Featured researches published by xiang Li.
Chaos | 2016
Jing Yuan; Lixiang Li; Haipeng Peng; Jürgen Kurths; Jinghua Xiao; Yixian Yang
The percolation for interdependent networks with identical dependency map follows a second-order phase transition which is exactly the same with percolation on a single network, while percolation for random dependency follows a first-order phase transition. In real networks, the dependency relations between networks are neither identical nor completely random. Thus in this paper, we study the influence of randomness for dependency maps on the robustness of interdependent lattice networks. We introduce approximate entropy(ApEn) as the measure of randomness of the dependency maps. We find that there is critical ApEnc below which the percolation is continuous, but for larger ApEn, it is a first-order transition. With the increment of ApEn, the pc increases until ApEn reaching ApEnc′ and then remains almost constant. The time scale of the system shows rich properties as ApEn increases. Our results uncover that randomness is one of the important factors that lead to cascading failures of spatially interdependent networks.
Neurocomputing | 2018
Zigang Chen; Lixiang Li; Haipeng Peng; Yuhong Liu; Yixian Yang
Abstract In this paper, we propose a General Non-negative Matrix Factorization based on the left Semi-Tensor Product (lGNMF) and the General Non-negative Matrix Factorization based on the right Semi-Tensor Product (rGNMF), which factorize an input non-negative matrix into two non-negative matrices of lower ranks based on gradient method. In particular, the proposed models are able to remove the dimension matching constraints required by conventional NMF models. Both theoretical derivation and experimental results show that the conventional NMF is a special case of the proposed lGNMF and rGNMF. We find the method for the best efficacy of the image restoration in lGNMF and rGNMF by experiments on baboon and lenna images. Moreover, inspired by the Incremental Non-negative Matrix Factorization (INMF), we propose the Incremental lGNMF (IlGNMF) and Incremental rGNMF (IrGNMF), We also conduct the experiments on JAFFE database and ORL database, and find that IlGNMF and IrGNMF realize saving storage space and reducing computation time in incremental facial training.
international conference on swarm intelligence | 2013
Yu-Ying Li; Lixiang Li; Haipeng Peng
This paper presents an improved chaotic ant swarm (ICAS) by introducing three strategies, which are comprehensive learning strategy, search bound strategy and refinement search strategy, into chaotic ant swarm (CAS) for solving optimization problems. The first two strategies are employed to update ants’ positions, which preserve the diversity of the swarm so that the ICAS discourages premature convergence. In addition, the refinement search strategy is adopted to increase the solution quality in the ICAS. Simulations show that the ICAS significantly enhances solution accuracy and convergence stability of the CAS.
Chaos Solitons & Fractals | 2006
Lixiang Li; Yixian Yang; Haipeng Peng; Xiangdong Wang
Chaos Solitons & Fractals | 2009
Hui Zhu; Lixiang Li; Ying Zhao; Yu Guo; Yixian Yang
Chaos Solitons & Fractals | 2009
Yu-Ying Li; Qiao-Yan Wen; Lixiang Li; Haipeng Peng
Physica A-statistical Mechanics and Its Applications | 2011
Shudong Li; Lixiang Li; Yixian Yang
Physics Letters A | 2004
Lixiang Li; Haipeng Peng; Xiangdong Wang; Yixian Yang
Chaos Solitons & Fractals | 2007
Haipeng Peng; Lixiang Li; Yixian Yang; Xiaohong Zhang
Physica A-statistical Mechanics and Its Applications | 2018
Zhen Su; Lixiang Li; Jinghua Xiao; Boris Podobnik; H. Eugene Stanley