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» On sparse signal representations
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ICASSP
2008
IEEE
15 years 6 months ago
Subspace compressive detection for sparse signals
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
Zhongmin Wang, Gonzalo R. Arce, Brian M. Sadler
DAGM
2001
Springer
15 years 4 months ago
Scale Adaptive Filtering Derived from the Laplace Equation
In this paper, we present a new approach to scale-space which is derived from the 3D Laplace equation instead of the heat equation. The resulting lowpass and bandpass filters are...
Michael Felsberg, Gerald Sommer
CORR
2008
Springer
99views Education» more  CORR 2008»
14 years 12 months ago
A New Trend in Optimization on Multi Overcomplete Dictionary toward Inpainting
1 Recently, great attention was intended toward overcomplete dictionaries and the sparse representations they can provide. In a wide variety of signal processing problems, sparsity...
Seyyed Majid Valiollahzadeh, Mohammad Nazari, Mass...
ICCV
2011
IEEE
13 years 12 months ago
Centralized Sparse Representation for Image Restoration
This paper proposes a novel sparse representation model called centralized sparse representation (CSR) for image restoration tasks. In order for faithful image reconstruction, it ...
Weisheng Dong, Lei Zhang, Guangming Shi
NIPS
2003
15 years 1 months ago
Sparse Representation and Its Applications in Blind Source Separation
In this paper, sparse representation (factorization) of a data matrix is first discussed. An overcomplete basis matrix is estimated by using the K−means method. We have proved ...
Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari, Se...