17 search results - page 3 / 4 » Reconstruction of Multidimensional Signals from Irregular No... |
GRC
2008
IEEE
13 years 6 months ago
2008
IEEE
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
ICIP
2005
IEEE
14 years 7 months ago
2005
IEEE
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant " space, ...
ICASSP
2010
IEEE
13 years 6 months ago
2010
IEEE
This paper addresses the problem of the interpolation of 2-d spherical signals from non-uniformly sampled and noisy data. We propose a graph-based regularization algorithm to impr...
TSP
2010
13 years 14 days ago
2010
This paper puts to use concepts and tools introduced in Part I to address a wide spectrum of noncausal sampling and reconstruction problems. Particularly, we follow the systemtheor...
TSP
2008
13 years 5 months ago
2008
Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant" space, wh...