117 search results - page 3 / 24 » Sparse reconstruction by separable approximation |
ICA
2004
Springer
15 years 3 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...
80
Voted
RT
1999
Springer
15 years 1 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
15 years 4 months 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
14 years 4 months 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
15 years 4 months ago
2008
IEEE
Abstract—We develop neurally plausible local competitive algorithms (LCAs) for reconstructing compressively sensed images. Reconstruction requires solving a sparse approximation ...