A Dynamical System With Fixed Convergence Time for Sparse Recovery
The sparse recovery (SR) algorithm, under the premise that signals are sparse, can be divided into two categories. One is a digital discrete method implemented via lots of iterative computations and the other is a continuous method implemented via analog circuits, which is usually faster. In this pa...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8638783/ |
| _version_ | 1818854598171951104 |
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| author | Junying Ren Lei Yu Yulun Jiang Jean-Pierre Barbot Hong Sun |
| author_facet | Junying Ren Lei Yu Yulun Jiang Jean-Pierre Barbot Hong Sun |
| author_sort | Junying Ren |
| collection | DOAJ |
| description | The sparse recovery (SR) algorithm, under the premise that signals are sparse, can be divided into two categories. One is a digital discrete method implemented via lots of iterative computations and the other is a continuous method implemented via analog circuits, which is usually faster. In this paper, we focus on the continuous method and propose a fixed-time convergence dynamical system. Compared with the existing system, it dynamically allocates the exponent according to time-varying elements of the system state, avoiding possible mismatches between the fixed exponent and some elements. |
| first_indexed | 2024-12-19T07:55:15Z |
| format | Article |
| id | doaj.art-c13ff51922324c3e93adbbcf896a8e6b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T07:55:15Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c13ff51922324c3e93adbbcf896a8e6b2022-12-21T20:30:02ZengIEEEIEEE Access2169-35362019-01-017218442185010.1109/ACCESS.2019.28974888638783A Dynamical System With Fixed Convergence Time for Sparse RecoveryJunying Ren0Lei Yu1https://orcid.org/0000-0002-7329-4631Yulun Jiang2Jean-Pierre Barbot3Hong Sun4School of Electronic and Information, Wuhan University, Wuhan, ChinaSchool of Electronic and Information, Wuhan University, Wuhan, ChinaSchool of Electronic and Information, Wuhan University, Wuhan, ChinaQuartz EA 7393, ENSEA, Cergy-Pontoise, FranceSchool of Electronic and Information, Wuhan University, Wuhan, ChinaThe sparse recovery (SR) algorithm, under the premise that signals are sparse, can be divided into two categories. One is a digital discrete method implemented via lots of iterative computations and the other is a continuous method implemented via analog circuits, which is usually faster. In this paper, we focus on the continuous method and propose a fixed-time convergence dynamical system. Compared with the existing system, it dynamically allocates the exponent according to time-varying elements of the system state, avoiding possible mismatches between the fixed exponent and some elements.https://ieeexplore.ieee.org/document/8638783/Sparse recoverydynamical systemfixed-time convergence |
| spellingShingle | Junying Ren Lei Yu Yulun Jiang Jean-Pierre Barbot Hong Sun A Dynamical System With Fixed Convergence Time for Sparse Recovery IEEE Access Sparse recovery dynamical system fixed-time convergence |
| title | A Dynamical System With Fixed Convergence Time for Sparse Recovery |
| title_full | A Dynamical System With Fixed Convergence Time for Sparse Recovery |
| title_fullStr | A Dynamical System With Fixed Convergence Time for Sparse Recovery |
| title_full_unstemmed | A Dynamical System With Fixed Convergence Time for Sparse Recovery |
| title_short | A Dynamical System With Fixed Convergence Time for Sparse Recovery |
| title_sort | dynamical system with fixed convergence time for sparse recovery |
| topic | Sparse recovery dynamical system fixed-time convergence |
| url | https://ieeexplore.ieee.org/document/8638783/ |
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