Sciweavers

534 search results - page 12 / 107
» Data Separation by Sparse Representations
Sort
View
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 9 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
NECO
2010
154views more  NECO 2010»
13 years 7 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
IPPS
2008
IEEE
14 years 3 months ago
On the representation and multiplication of hypersparse matrices
Multicore processors are marking the beginning of a new era of computing where massive parallelism is available and necessary. Slightly slower but easy to parallelize kernels are ...
Aydin Buluç, John R. Gilbert
ICASSP
2011
IEEE
13 years 20 days ago
Dictionary learning of convolved signals
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...
Daniele Barchiesi, Mark D. Plumbley
ICIP
2009
IEEE
14 years 10 months ago
Reconstructing Ft-ir Spectroscopic Imaging Data With A Sparse Prior
Fourier Transform Infrared (FT-IR) spectroscopic imaging is a potentially valuable tool for diagnosing breast and prostate cancer, but its clinical deployment is limited due to lo...