117 search results - page 3 / 24 » Sparse reconstruction by separable approximation |
ICA
2004
Springer
13 years 11 months ago
2004
Springer
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
RT
1999
Springer
13 years 10 months ago
1999
Springer
A separable decomposition of bidirectional reflectance distributions (BRDFs) is used to implement arbitrary reflectances from point sources on existing graphics hardware. Two-dim...
ICASSP
2008
IEEE
14 years 13 days ago
2008
IEEE
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
TSP
2010
13 years 21 days ago
2010
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
CISS
2008
IEEE
14 years 14 days ago
2008
IEEE
Abstract—We develop neurally plausible local competitive algorithms (LCAs) for reconstructing compressively sensed images. Reconstruction requires solving a sparse approximation ...