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CORR
2010
Springer
172views Education» more  CORR 2010»
13 years 8 months ago
The MUSIC Algorithm for Sparse Objects: A Compressed Sensing Analysis
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
Albert Fannjiang
CORR
2008
Springer
161views Education» more  CORR 2008»
13 years 6 months ago
Compressed Sensing of Analog Signals
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...
Yonina C. Eldar
ICIP
2010
IEEE
13 years 5 months ago
Streaming Compressive Sensing for high-speed periodic videos
The ability of Compressive Sensing (CS) to recover sparse signals from limited measurements has been recently exploited in computational imaging to acquire high-speed periodic and...
M. Salman Asif, Dikpal Reddy, Petros Boufounos, As...
CORR
2011
Springer
203views Education» more  CORR 2011»
13 years 2 months ago
Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
CORR
2011
Springer
259views Education» more  CORR 2011»
13 years 2 months ago
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range
Compressive sensing (CS) exploits the sparsity present in many common signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, ...
Mark A. Davenport, Jason N. Laska, John R. Treichl...