A Matrix Inversion Free Method for Computing Katz Centrality of Taipei Metro System Using Neumann Series

Author(s):  
Chien-Cheng Tseng ◽  
Su-Ling Lee
2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Lin Shao ◽  
Yunxiao Zu

Due to large numbers of antennas and users, matrix inversion is complicated in linear precoding techniques for massive MIMO systems. Several approximated matrix inversion methods, including the Neumann series, have been proposed to reduce the complexity. However, the Neumann series does not converge fast enough. In this paper, to speed up convergence, a new joint Newton iteration and Neumann series method is proposed, with the first iteration result of Newton iteration method being employed to reconstruct the Neumann series. Then, a high probability convergence condition is established, which can offer useful guidelines for practical massive MIMO systems. Finally, simulation examples are given to demonstrate that the new joint Newton iteration and Neumann series method has a faster convergence rate compared to the previous Neumann series, with almost no increase in complexity when the iteration number is greater than or equal to 2.


2017 ◽  
Vol 5 (2) ◽  
pp. 833-840
Author(s):  
Seoung-bum Kim ◽  
Hwa-Jeong Tak ◽  
Jonghee Lee
Keyword(s):  

Author(s):  
Ginestra Bianconi

Defining the centrality of nodes and layers in multilayer networks is of fundamental importance for a variety of applications from sociology to biology and finance. This chapter presents the state-of-the-art centrality measures able to characterize the centrality of nodes, the influences of layers or the centrality of replica nodes in multilayer and multiplex networks. These centrality measures include modifications of the eigenvector centrality, Katz centrality, PageRank centrality and Communicability to the multilayer network scenario. The chapter provides a comprehensive description of the research of the field and discusses the main advantages and limitations of the different definitions, allowing the readers that wish to apply these techniques to choose the most suitable definition for his or her case study.


2021 ◽  
Vol 573 ◽  
pp. 125957
Author(s):  
Kangli Zhu ◽  
Haodong Yin ◽  
YunChao Qu ◽  
Jianjun Wu

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