@inproceedings{7d6b810a01be439696d76a86737c32cc,
title = "Distributed compressive sensing for correlated information sources",
abstract = "The abstract should summarize the contents of the paper and should Distributed Compressive Sensing (DCS) improves the signal recovery performance of multi signal ensembles by exploiting both intra- and inter-signal correlation and sparsity structure. In this paper, we propose a novel algorithm, which improves detection performance even without a priori-knowledge on the correlation structure for arbitrarily correlated sparse signal. Numerical results verify that the propose algorithm reduces the required number of measurements for correlated sparse signal detection compared to the existing DCS algorithm.",
author = "Jeonghun Park and Seunggye Hwang and Janghoon Yang and Kitae Bae and Hoon Ko and Kim, \{Dong Ku\}",
note = "Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017.; 7th International Conference on Big Data Technologies and Applications, BDTA 2016 ; Conference date: 17-11-2016 Through 18-11-2016",
year = "2017",
doi = "10.1007/978-3-319-58967-1\_15",
language = "English (US)",
isbn = "9783319589664",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Verlag",
pages = "130--137",
editor = "Jung, \{Jason J.\} and Pankoo Kim",
booktitle = "Big Data Technologies and Applications - 7th International Conference, BDTA 2016, Proceedings",
address = "Germany",
}