THE NETWORK NULLSPACE PROPERTY FOR COMPRESSED SENSING OF BIG DATA OVER NETWORKS

被引：0
|
作者：
Hulsebos, Madelon [1 ]
Jung, Alexander [2 ]
机构：
[1] Delft Univ Technol, Dept Comp Sci, Delft, Netherlands
[2] Aalto Univ, Dept Comp Sci, Espoo, Finland
来源：
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2018年
关键词：
compressed sensing; big data; semi-supervised learning; complex networks; convex optimization;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
We present a novel condition, which we term the network nullspace property, which ensures accurate recovery of graph signals representing massive network-structured datasets from few signal values. The network nullspace property couples the cluster structure of the underlying network-structure with the geometry of the sampling set. Our results can be used to design efficient sampling strategies based on the network topology.
引用
收藏
页码：4549 / 4553
页数：5
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