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Fast graph sampling set selection using gershgorin disc alignment

Abstract:

Graph sampling set selection, where a subset of nodes are chosen to collect samples to reconstruct a bandlimited or smooth graph signal, is a fundamental problem in graph signal processing (GSP). Previous works employ an unbiased least square (LS) signal reconstruction scheme and select samples via expensive extreme eigenvector computation. Instead, we assume a biased graph Laplacian regularization (GLR) based scheme that solves a system of linear equations for reconstruction. We then choose ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/tsp.2020.2981202

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Sub department:
Mathematical Institute
Oxford college:
Christ Church
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
IEEE Transactions on Signal Processing Journal website
Volume:
68
Pages:
2419 - 2434
Publication date:
2020-03-18
Acceptance date:
2020-03-03
DOI:
EISSN:
1941-0476
ISSN:
1053-587X
Language:
English
Keywords:
Pubs id:
1099444
Local pid:
pubs:1099444
Deposit date:
2020-04-10

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