Perturbations of Compressed Data Separation With Redundant Tight Frames
In the era of big data, the multi-modal data can be seen everywhere. Research on such data has attracted extensive attention in the past few years. In this paper, we investigate the perturbations of compressed data separation with redundant tight frames via Φ̃-Iq-minimization....
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doaj-b742c505b39244fb8d867454c385b1d12021-03-29T21:03:05ZengIEEEIEEE Access2169-35362018-01-016358443585610.1109/ACCESS.2018.28510198398197Perturbations of Compressed Data Separation With Redundant Tight FramesFeng Zhang0https://orcid.org/0000-0003-1000-8877Jianjun Wang1Yao Wang2Jianwen Huang3https://orcid.org/0000-0003-3792-1383Wendong Wang4School of Mathematics and Statistics, Southwest University, Chongqing, ChinaSchool of Mathematics and Statistics, Southwest University, Chongqing, ChinaSchool of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, ChinaSchool of Mathematics and Statistics, Southwest University, Chongqing, ChinaSchool of Mathematics and Statistics, Southwest University, Chongqing, ChinaIn the era of big data, the multi-modal data can be seen everywhere. Research on such data has attracted extensive attention in the past few years. In this paper, we investigate the perturbations of compressed data separation with redundant tight frames via Φ̃-Iq-minimization. By exploiting the properties of the redundant tight frame and the perturbation matrix, i.e., mutual coherence, null space property, and restricted isometry property, the condition on reconstruction of sparse signal with redundant tight frames is established, and the error estimation between the local optimal solution and the original signal is also provided. Numerical experiments are carried out to show that Φ̃-Iq-minimization is robust and stable for the reconstruction of sparse signal with redundant tight frames. To our knowledge, our works may be the first study concerning the perturbations of the measurement matrix and the redundant tight frame for compressedhttps://ieeexplore.ieee.org/document/8398197/Compressed data separationperturbationnull space propertyrestricted isometry property |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Feng Zhang Jianjun Wang Yao Wang Jianwen Huang Wendong Wang |
spellingShingle |
Feng Zhang Jianjun Wang Yao Wang Jianwen Huang Wendong Wang Perturbations of Compressed Data Separation With Redundant Tight Frames IEEE Access Compressed data separation perturbation null space property restricted isometry property |
author_facet |
Feng Zhang Jianjun Wang Yao Wang Jianwen Huang Wendong Wang |
author_sort |
Feng Zhang |
title |
Perturbations of Compressed Data Separation With Redundant Tight Frames |
title_short |
Perturbations of Compressed Data Separation With Redundant Tight Frames |
title_full |
Perturbations of Compressed Data Separation With Redundant Tight Frames |
title_fullStr |
Perturbations of Compressed Data Separation With Redundant Tight Frames |
title_full_unstemmed |
Perturbations of Compressed Data Separation With Redundant Tight Frames |
title_sort |
perturbations of compressed data separation with redundant tight frames |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2018-01-01 |
description |
In the era of big data, the multi-modal data can be seen everywhere. Research on such data has attracted extensive attention in the past few years. In this paper, we investigate the perturbations of compressed data separation with redundant tight frames via Φ̃-Iq-minimization. By exploiting the properties of the redundant tight frame and the perturbation matrix, i.e., mutual coherence, null space property, and restricted isometry property, the condition on reconstruction of sparse signal with redundant tight frames is established, and the error estimation between the local optimal solution and the original signal is also provided. Numerical experiments are carried out to show that Φ̃-Iq-minimization is robust and stable for the reconstruction of sparse signal with redundant tight frames. To our knowledge, our works may be the first study concerning the perturbations of the measurement matrix and the redundant tight frame for compressed |
topic |
Compressed data separation perturbation null space property restricted isometry property |
url |
https://ieeexplore.ieee.org/document/8398197/ |
work_keys_str_mv |
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