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- Richard G. Baraniuk, Volkan Cevher, Marco F. Duarte, Chinmay Hegde
- IEEE Transactions on Information Theory
- 2010

Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for the acquisition of sparse or compressible signals that can be well approximated by just K Â¿ N elements from an Nâ€¦ (More)

- Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Justin K. Romberg, Richard G. Baraniuk
- IEEE Transactions on Information Theory
- 2010

Wideband analog signals push contemporary analog-to-digital conversion (ADC) systems to their performance limits. In many applications, however, sampling at the Nyquist rate is inefficient becauseâ€¦ (More)

- Marco F. Duarte, Yonina C. Eldar
- IEEE Transactions on Signal Processing
- 2011

Compressed sensing (CS) is an emerging field that has attracted considerable research interest over the past few years. Previous review articles in CS limit their scope to standardâ€¦ (More)

- Marco F. Duarte, Yu Hen Hu
- J. Parallel Distrib. Comput.
- 2004

The task of classifying the types of moving vehicles in a distributed, wireless sensor network is investigated. Specifically, based on an extensive real world experiment, we have compiled a datasetâ€¦ (More)

Compressed sensing is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. In this paper weâ€¦ (More)

- Marco F. Duarte, Richard G. Baraniuk
- IEEE Transactions on Image Processing
- 2012

Compressive sensing (CS) is an emerging approach for the acquisition of signals having a sparse or compressible representation in some basis. While the CS literature has mostly focused on problemsâ€¦ (More)

Compressive sensing is a signal acquisition framework based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable recovery. In thisâ€¦ (More)

- Jason N. Laska, Sami Kirolos, Marco F. Duarte, Tamer Ragheb, Richard G. Baraniuk, Yehia Massoud
- 2007 IEEE International Symposium on Circuits andâ€¦
- 2007

The new theory of compressive sensing enables direct analog-to-information conversion of compressible signals at sub-Nyquist acquisition rates. The authors develop new theory, algorithms, performanceâ€¦ (More)

- Dharmpal Takhar, Jason N. Laska, +5 authors Richard G. Baraniuk
- Computational Imaging
- 2006

Compressive Sensing is an emerging field based on the revelation that a small number of linear projections of a compressible signal contain enough information for reconstruction and processing. Itâ€¦ (More)

- M. A. Davenport, M. F. Duarte, +5 authors Gitta Kutyniok

The consecutive numbering of the publications is determined by their chronological order. The aim of this preprint series is to make new research rapidly available for scientific discussion.â€¦ (More)