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» On sparse signal representations
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ICASSP
2010
IEEE
15 years 2 days ago
Learning sparse systems at sub-Nyquist rates: A frequency-domain approach
We propose a novel algorithm for sparse system identification in the frequency domain. Key to our result is the observation that the Fourier transform of the sparse impulse respo...
Martin McCormick, Yue M. Lu, Martin Vetterli
ECCV
2008
Springer
16 years 1 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
ICASSP
2009
IEEE
15 years 6 months ago
A compressive sensing approach to object-based surveillance video coding
This paper studies the feasibility and investigates various choices in the application of compressive sensing (CS) to object-based surveillance video coding. The residual object e...
Divya Venkatraman, Anamitra Makur
CORR
2008
Springer
161views Education» more  CORR 2008»
14 years 10 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
CORR
2007
Springer
116views Education» more  CORR 2007»
14 years 12 months ago
Non-Coherent Capacity and Reliability of Sparse Multipath Channels in the Wideband Regime
— In contrast to the prevalent assumption of rich multipath in information theoretic analysis of wireless channels, physical channels exhibit sparse multipath, especially at larg...
Gautham Hariharan, Akbar M. Sayeed