Publication
High Resolution Spectral Estimation using BP via Compressive Sensing
| dc.contributor.author | Duarte, Isabel | |
| dc.contributor.author | Vieira, José M. N. | |
| dc.contributor.author | Ferreira, Paulo J S G | |
| dc.contributor.author | Albuquerque, Daniel | |
| dc.date.accessioned | 2015-01-09T10:09:55Z | |
| dc.date.available | 2015-01-09T10:09:55Z | |
| dc.date.issued | 2012-10 | |
| dc.description.abstract | In this paper we propose a method based on compressed sensing (CS) for estimating the spectrum of a signal written as a linear combination of a small number of sinusoids. In the case of finite-length signals, the Fourier coefficients are not exactly sparse due to the leakage effect if the frequency is not a multiple of the fundamental frequency; To overcome this problem our algorithm transform the DFT basis into a frame with a larger number of vectors, by inserting columns between some of the initial ones. The algorithm applies Basis Pursuit (BP) to estimate the sinusoids amplitude, phase and frequency. | por |
| dc.identifier.isbn | 978-988-19251-6-9 | |
| dc.identifier.uri | http://hdl.handle.net/10400.19/2506 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.publisher | S. I. Ao and Craig Douglas and W. S. Grundfest and Jon Burgstone | por |
| dc.subject | Basis Pursuit | por |
| dc.subject | compressive sensing | por |
| dc.subject | spectral estimation | por |
| dc.subject | sparse representations | por |
| dc.title | High Resolution Spectral Estimation using BP via Compressive Sensing | por |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | San Francisco, USA | por |
| oaire.citation.endPage | 704 | por |
| oaire.citation.startPage | 699 | por |
| oaire.citation.title | Proceedings of the World Congress on Engineering and Computer Science 2012 | por |
| oaire.citation.volume | I | por |
| rcaap.rights | closedAccess | por |
| rcaap.type | article | por |