@inproceedings{73f80b1a86dd41db81ea3a264986d7f6,
title = "Compressed sensing with prior information via maximizing correlation",
abstract = "Compressed sensing (CS) with prior information concerns the problem of reconstructing a sparse signal with the aid of a similar signal which is known beforehand. We consider a new approach to integrate the prior information into CS via maximizing the correlation between the prior knowledge and the desired signal. We then present a geometric analysis for the proposed method under sub-Gaussian measurements. Our results reveal that if the prior information is good enough, then the proposed approach can improve the performance of the standard CS. Simulations are provided to verify our results.",
keywords = "Compressed sensing, Gaussian width, Maximizing correlation, Prior information",
author = "Xu Zhang and Wei Cui and Yulong Liu",
year = "2017",
month = aug,
day = "9",
doi = "10.1109/ISIT.2017.8006522",
language = "English",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "221--225",
booktitle = "2017 IEEE International Symposium on Information Theory, ISIT 2017",
address = "United States",
note = "2017 IEEE International Symposium on Information Theory, ISIT 2017 ; Conference date: 25-06-2017 Through 30-06-2017",
}