IEICE TRANSACTIONS on Fundamentals
Combining Stability and Robustness in Reconstruction Problems via lq (0 < q ≤ 1) Quasinorm Using Compressive Sensing
Summary :
Compressive sensing is a promising technique in data acquisition field. A central problem in compressive sensing is that for a given sparse signal, we wish to recover it accurately, efficiently and stably from very few measurements. Inspired by mathematical analysis, we introduce a combining scheme between stability and robustness in reconstruction problems using compressive sensing. By choosing appropriate parameters, we are able to construct a condition for reconstruction map to perform properly.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E97-A No.3 pp.894-898
- Publication Date
- 2014/03/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E97.A.894
- Type of Manuscript
- LETTER
- Category
- Communication Theory and Signals
Authors
Thu L. N. NGUYEN
Soongsil University
Yoan SHIN
Soongsil University
Keyword
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Thu L. N. NGUYEN, Yoan SHIN, "Combining Stability and Robustness in Reconstruction Problems via lq (0 < q ≤ 1) Quasinorm Using Compressive Sensing" in IEICE TRANSACTIONS on Fundamentals,
vol. E97-A, no. 3, pp. 894-898, March 2014, doi: 10.1587/transfun.E97.A.894.
Abstract: Compressive sensing is a promising technique in data acquisition field. A central problem in compressive sensing is that for a given sparse signal, we wish to recover it accurately, efficiently and stably from very few measurements. Inspired by mathematical analysis, we introduce a combining scheme between stability and robustness in reconstruction problems using compressive sensing. By choosing appropriate parameters, we are able to construct a condition for reconstruction map to perform properly.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E97.A.894/_p
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@ARTICLE{e97-a_3_894,
author={Thu L. N. NGUYEN, Yoan SHIN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Combining Stability and Robustness in Reconstruction Problems via lq (0 < q ≤ 1) Quasinorm Using Compressive Sensing},
year={2014},
volume={E97-A},
number={3},
pages={894-898},
abstract={Compressive sensing is a promising technique in data acquisition field. A central problem in compressive sensing is that for a given sparse signal, we wish to recover it accurately, efficiently and stably from very few measurements. Inspired by mathematical analysis, we introduce a combining scheme between stability and robustness in reconstruction problems using compressive sensing. By choosing appropriate parameters, we are able to construct a condition for reconstruction map to perform properly.},
keywords={},
doi={10.1587/transfun.E97.A.894},
ISSN={1745-1337},
month={March},}
Copy
TY - JOUR
TI - Combining Stability and Robustness in Reconstruction Problems via lq (0 < q ≤ 1) Quasinorm Using Compressive Sensing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 894
EP - 898
AU - Thu L. N. NGUYEN
AU - Yoan SHIN
PY - 2014
DO - 10.1587/transfun.E97.A.894
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E97-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2014
AB - Compressive sensing is a promising technique in data acquisition field. A central problem in compressive sensing is that for a given sparse signal, we wish to recover it accurately, efficiently and stably from very few measurements. Inspired by mathematical analysis, we introduce a combining scheme between stability and robustness in reconstruction problems using compressive sensing. By choosing appropriate parameters, we are able to construct a condition for reconstruction map to perform properly.
ER -
English
