Greedy recovery of sparse signals with dynamically varying support
- Authors
- Lim, Sun Hong; Yoo, Jin Hyeok; Kim, Sun woo; Choi, Jun Won
- Issue Date
- Nov-2018
- Publisher
- European Signal Processing Conference, EUSIPCO
- Citation
- European Signal Processing Conference, v.2018, no.09, pp.578 - 582
- Indexed
- SCOPUS
- Journal Title
- European Signal Processing Conference
- Volume
- 2018
- Number
- 09
- Start Page
- 578
- End Page
- 582
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/5253
- DOI
- 10.23919/EUSIPCO.2018.8553450
- ISSN
- 2219-5491
- Abstract
- In this paper, we propose a low-complexity greedy recovery algorithm which can recover sparse signals with time-varying support. We consider the scenario where the support of the signal (i.e., the indices of nonzero elements) varies smoothly with certain temporal correlation. We model the indices of support as discrete-state Markov random process. Then, we formulate the signal recovery problem as joint estimation of the set of the support indices and the amplitude of nonzero entries based on the multiple measurement vectors. We successively identify the element of the support based on the maximum a posteriori (MAP) criteria and subtract the reconstructed signal component for detection of the next element of the support. Our numerical evaluation shows that the proposed algorithm achieves satisfactory recovery performance at low computational complexity.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 전기공학전공 > 1. Journal Articles
- 서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/5253)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.