## 抄録

A new theory known as compressed sensing considers the problem to acquire and recover a sparse signal from its linear measurements. In this paper, we propose a new support recovery algorithm from noisy measurements based on the linear programming (LP). LP is widely used to estimate sparse signals, however, we focus on the problem to recover the support of sparse signals rather than the problem to estimate sparse signals themselves. First, we derive an integer linear programming (ILP) formulation for the support recovery problem. Then we obtain the LP based support recovery algorithm by relaxing the ILP. The proposed LP based recovery algorithm has an attracting property that the output of the algorithm is guaranteed to be the maximum a posteiori (MAP) estimate when it is integer valued. We compare the performance of the proposed algorithm to a state-of-the-art algorithm named sparse matching pursuit (SMP) via numerical simulations.

本文言語 | English |
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ホスト出版物のタイトル | Proceedings of 2016 International Symposium on Information Theory and Its Applications, ISITA 2016 |

出版社 | Institute of Electrical and Electronics Engineers Inc. |

ページ | 270-274 |

ページ数 | 5 |

ISBN（電子版） | 9784885523090 |

出版ステータス | Published - 2017 2月 2 |

イベント | 3rd International Symposium on Information Theory and Its Applications, ISITA 2016 - Monterey, United States 継続期間: 2016 10月 30 → 2016 11月 2 |

### Other

Other | 3rd International Symposium on Information Theory and Its Applications, ISITA 2016 |
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国/地域 | United States |

City | Monterey |

Period | 16/10/30 → 16/11/2 |

## ASJC Scopus subject areas

- コンピュータ ネットワークおよび通信
- ハードウェアとアーキテクチャ
- 情報システム
- 信号処理
- 図書館情報学