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Adaptive sampling for fast sparsity pattern recovery

Author
Ramirez, F.; Matas, D.; Lamarca, M.
Type of activity
Presentation of work at congresses
Name of edition
19th European Signal Processing Conference
Date of publication
2011
Presentation's date
2011-09-01
Book of congress proceedings
EUSIPCO 2011: 19th European Signal Processing Conference
First page
348
Last page
352
Repository
http://hdl.handle.net/2117/18421 Open in new window
URL
http://www.eurasip.org/Proceedings/Eusipco/Eusipco2011/papers/1569424357.pdf Open in new window
Abstract
In this paper we propose a low complexity adaptive algorithm for lossless compressive sampling and reconstruction of sparse signals. Consider a sparse non-negative real signal x containing only 𝑘 << 𝑛 non-zero values. The sampling process obtains 𝑚 measurements by a linear projection y = Ax and, in order to minimize the complexity, we quantize them to binary values. We also define the measurement matrix A to be binary and sparse, enabling the use of a simple message passing algorithm ov...
Citation
Ramirez, F.; Matas, D.; Lamarca, M. Adaptive sampling for fast sparsity pattern recovery. A: European Signal Processing Conference. "EUSIPCO 2011: 19th European Signal Processing Conference". Barcelona: 2011, p. 348-352.
Group of research
SPCOM - Signal Processing and Communications Group

Participants

  • Ramirez Javega, Francisco  (author and speaker )
  • Matas Navarro, David  (author and speaker )
  • Lamarca Orozco, M. Meritxell  (author and speaker )

Attachments