@inproceedings{75b1c632785448caa8aee42ab9a55267,

title = "The network nullspace property for compressed sensing over networks",

abstract = "We study compressed sensing of graph signals defined over complex networks. In particular, we propose and analyze a convex optimization method for recovering smooth graph signals from a small number of samples. Assuming the true underlying graph signal to be constant over well connected subset of nodes (clusters), we derive a sufficient condition on the sampling set and network structure such that the proposed convex method is accurate. This condition, which we coin the network nullspace property, characterizes which nodes of the graph should be sampled in order to retain the full information about the underlying graph signal.",

keywords = "big data, complex networks, compressed sensing, convex optimzation, semisupervised learning",

author = "Alexander Jung and Ayelet Heimowitz and Eldar, {Yonina C.}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 12th International Conference on Sampling Theory and Applications, SampTA 2017 ; Conference date: 03-07-2017 Through 07-07-2017",

year = "2017",

month = sep,

day = "1",

doi = "10.1109/SAMPTA.2017.8024392",

language = "אנגלית",

series = "2017 12th International Conference on Sampling Theory and Applications, SampTA 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "644--648",

editor = "Gholamreza Anbarjafari and Andi Kivinukk and Gert Tamberg",

booktitle = "2017 12th International Conference on Sampling Theory and Applications, SampTA 2017",

address = "ארצות הברית",

}