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Algebraic Connectivity Estimation Based On Decentralized Inverse Power Iteration
Yue Wei, Hao Fang, Jie Chen, Bin Xin
The School of Automation, Beijing Institute of Technology, Beijing 100081
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Funding: 高等学校博士学科点专项科研基金 （No.20111101110011）
Opened online: 5 January 2016
Accepted by: none
Citation: Yue Wei, Hao Fang, Jie Chen.Algebraic Connectivity Estimation Based On Decentralized Inverse Power Iteration[OL]. [ 5 January 2016] http://en.paper.edu.cn/en_releasepaper/content/4673942
 
 
In this work we propose a new scheme to estimate the algebraic connectivity of the Laplacian matrix associated with the graph describing the network topology of a multi-agent system. We consider network topologies modelled by undirected graphs. The main idea is to propose a new decentralized conjugate gradient algorithm and a decentralized compound inverse power iteration scheme is built, in which the matrix inversion computation is replaced by solving the non-homogeneous linear equations relying on the proposed decentralized conjugate gradient algorithm. With this scheme, we can achieve a fast convergence rate in algebraic connectivity estimation by setting the parameter $mu$ properly. Simulation results demonstrate the effectiveness of the proposed scheme.
Keywords:Pattern recognition and intelligent system; Inverse power iteration; Decentralized estimation
 
 
 

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