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This paper proposes a sampling strategy for bandlimited graph signals over perturbed graph, in which we assume the edge between any pair of the nodes may be deleted randomly. Considering the mismatch between the true graph and the presumed graph, we derive the mean square error (MSE) of the reconstructed bandlimited graph signals. To minimize the MSE, we propose a greedy-based algorithm to obtain the optimal sampling set. Furthermore, we use Neumann series to avoid the pseudo-inverse computing. An efficient algorithm with low-complexity is thus proposed. Finally, numerical results show the superiority of our proposed algorithms over the other existing algorithms.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E103-A No.6 pp.845-849

- Publication Date
- 2020/06/01

- Publicized

- Online ISSN
- 1745-1337

- DOI
- 10.1587/transfun.2019EAL2135

- Type of Manuscript
- LETTER

- Category
- Graphs and Networks

Pei LI

Nanjing University of Posts and Telecommunications

Haiyang ZHANG

Singapore University of Technology and Design

Fan CHU

Nanjing University of Posts and Telecommunications

Wei WU

Nanjing University of Posts and Telecommunications

Juan ZHAO

Nanjing University of Posts and Telecommunications

Baoyun WANG

Nanjing University of Posts and Telecommunications

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Pei LI, Haiyang ZHANG, Fan CHU, Wei WU, Juan ZHAO, Baoyun WANG, "Sampling Set Selection for Bandlimited Signals over Perturbed Graph" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 6, pp. 845-849, June 2020, doi: 10.1587/transfun.2019EAL2135.

Abstract: This paper proposes a sampling strategy for bandlimited graph signals over perturbed graph, in which we assume the edge between any pair of the nodes may be deleted randomly. Considering the mismatch between the true graph and the presumed graph, we derive the mean square error (MSE) of the reconstructed bandlimited graph signals. To minimize the MSE, we propose a greedy-based algorithm to obtain the optimal sampling set. Furthermore, we use Neumann series to avoid the pseudo-inverse computing. An efficient algorithm with low-complexity is thus proposed. Finally, numerical results show the superiority of our proposed algorithms over the other existing algorithms.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019EAL2135/_p

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@ARTICLE{e103-a_6_845,

author={Pei LI, Haiyang ZHANG, Fan CHU, Wei WU, Juan ZHAO, Baoyun WANG, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={Sampling Set Selection for Bandlimited Signals over Perturbed Graph},

year={2020},

volume={E103-A},

number={6},

pages={845-849},

abstract={This paper proposes a sampling strategy for bandlimited graph signals over perturbed graph, in which we assume the edge between any pair of the nodes may be deleted randomly. Considering the mismatch between the true graph and the presumed graph, we derive the mean square error (MSE) of the reconstructed bandlimited graph signals. To minimize the MSE, we propose a greedy-based algorithm to obtain the optimal sampling set. Furthermore, we use Neumann series to avoid the pseudo-inverse computing. An efficient algorithm with low-complexity is thus proposed. Finally, numerical results show the superiority of our proposed algorithms over the other existing algorithms.},

keywords={},

doi={10.1587/transfun.2019EAL2135},

ISSN={1745-1337},

month={June},}

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TY - JOUR

TI - Sampling Set Selection for Bandlimited Signals over Perturbed Graph

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 845

EP - 849

AU - Pei LI

AU - Haiyang ZHANG

AU - Fan CHU

AU - Wei WU

AU - Juan ZHAO

AU - Baoyun WANG

PY - 2020

DO - 10.1587/transfun.2019EAL2135

JO - IEICE TRANSACTIONS on Fundamentals

SN - 1745-1337

VL - E103-A

IS - 6

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - June 2020

AB - This paper proposes a sampling strategy for bandlimited graph signals over perturbed graph, in which we assume the edge between any pair of the nodes may be deleted randomly. Considering the mismatch between the true graph and the presumed graph, we derive the mean square error (MSE) of the reconstructed bandlimited graph signals. To minimize the MSE, we propose a greedy-based algorithm to obtain the optimal sampling set. Furthermore, we use Neumann series to avoid the pseudo-inverse computing. An efficient algorithm with low-complexity is thus proposed. Finally, numerical results show the superiority of our proposed algorithms over the other existing algorithms.

ER -