TY - JOUR
T1 - Sampling signals from a union of subspaces
T2 - A new perspective for the extension of this theory
AU - Lu, Yue M.
AU - Do, Minh N.
N1 - This work was supported by the U.S. National Science Foundation under Grants CCF-0237633 (CAREER) and CCF-0635234.
the Ph.D. degree in electrical engineering from the University of Illinois at Urbana-Champaign in 2007. He is now with the Audio-Visual Communications Laboratory at the Swiss Federal Institute of Technology Lausanne, (EPFL) Switzerland. His research interests include sensor networks, geometrical signal representations, and sampling theory. He received the Most Innovative Paper Award of IEEE International Conference on Image Processing (ICIP) in 2006 and the Student Paper Award of IEEE ICIP in 2007. Minh N. Do ([email protected]) received the B.Eng. degree in computer engineering from the University of Canberra, Australia, and the Dr. Sci. degree in communication systems from the Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland, in 2001. He has since been an assistant professor with the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (UIUC). His research interests include multiscale geometric analysis, computational imaging, and visual information representation. He received the best doctoral thesis award from EPFL in 2001, a CAREER award from the National Science Foundation in 2003, and a Xerox Award for Faculty Research from UIUC in 2007.
PY - 2008/3
Y1 - 2008/3
N2 - A recent work on sampling signals has been about finite rate of innovation, which studies several specific classes of signals in the form of a certain form of equation in observed signals, including streams of Diracs and piecewise polynomials. A result of the finite rate of innovation sampling work is to demonstrate that these classes of bandlimited signals can be uniformly sampled at a low given rate and then perfectly reconstructed by using efficient algorithms based on annihilating filter techniques. The recent work also showed the conditions for invertible and stable sampling and derived the minimum sampling requirement. It showed that the recent work on sampling signals are more efficient than the minimum sampling rate dictated by classical sampling results that consider only spaces that are single.
AB - A recent work on sampling signals has been about finite rate of innovation, which studies several specific classes of signals in the form of a certain form of equation in observed signals, including streams of Diracs and piecewise polynomials. A result of the finite rate of innovation sampling work is to demonstrate that these classes of bandlimited signals can be uniformly sampled at a low given rate and then perfectly reconstructed by using efficient algorithms based on annihilating filter techniques. The recent work also showed the conditions for invertible and stable sampling and derived the minimum sampling requirement. It showed that the recent work on sampling signals are more efficient than the minimum sampling rate dictated by classical sampling results that consider only spaces that are single.
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U2 - 10.1109/MSP.2007.914999
DO - 10.1109/MSP.2007.914999
M3 - Article
AN - SCOPUS:85032750886
SN - 1053-5888
VL - 25
SP - 41
EP - 47
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 2
ER -