Distributed algorithms to determine eigenvectors of matrices on spatially distributed networks

Nazar Emirov, Cheng Cheng, Qiyu Sun, Zhihua Qu

Eigenvectors of matrices on a network have been used for understanding spectral clustering and influence of a vertex. For matrices with small geodesic-width, we propose a distributed iterative algorithm in this letter to find eigenvectors associated with their given eigenvalues. We also consider the implementation of the proposed algorithm at the vertex/agent level in a spatially distributed network.

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