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초록
In this paper, we propose an algorithm referred to as multipath matching pursuit (MMP) that investigates multiple promising candidates to recover sparse signals from compressed measurements. Our method is inspired by the fact that the problem to find the candidate that minimizes the residual is readily modeled as a combinatoric tree search problem and the greedy search strategy is a good fit for solving this problem. In the empirical results as well as the restricted isometry property-based performance guarantee, we show that the proposed MMP algorithm is effective in reconstructing original sparse signals for both noiseless and noisy scenarios.
키워드
Compressive sensing (CS); sparse signal recovery; orthogonal matching pursuit; greedy algorithm; restricted isometry property (RIP); Oracle estimator; RESTRICTED ISOMETRY PROPERTY; SIGNAL RECOVERY; RECONSTRUCTION
- 제목
- Multipath Matching Pursuit
- 저자
- Kwon, Suhyuk (Seokbeop); Wang, Jian; Shim, Byonghyo
- 발행일
- 2014-05
- 유형
- Article
- 권
- 60
- 호
- 5
- 페이지
- 2986 ~ 3001