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ICPR
2010
IEEE
10 years 1 months ago
Compressing Sparse Feature Vectors Using Random Ortho-Projections
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...
Esa Rahtu, Mikko Salo, Janne Heikkilä
CORR
2011
Springer
148views Education» more  CORR 2011»
9 years 6 months ago
How well can we estimate a sparse vector?
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Emmanuel J. Candès, Mark A. Davenport
ICIP
2009
IEEE
9 years 9 months ago
A compressive-sensing based watermarking scheme for sparse image tampering identification
In this paper we describe a robust watermarking scheme for image tampering identification and localization. A compact representation of the image is first produced by assembling a...
Giuseppe Valenzise, Marco Tagliasacchi, Stefano Tu...
ICASSP
2008
IEEE
10 years 6 months ago
Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model
Compressive sensing aims to recover a sparse or compressible signal from a small set of projections onto random vectors; conventional solutions involve linear programming or greed...
Marco F. Duarte, Michael B. Wakin, Richard G. Bara...
CDC
2010
IEEE
112views Control Systems» more  CDC 2010»
9 years 6 months ago
An overview of recent results on the identification of sparse channels using random probes
In this paper, we collect and discuss some of the recent theoretical results on channel identification using a random probe sequence. These results are part of the body of work kno...
Justin Romberg
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