Quantitative Error Analysis for the Reconstruction of Derivatives
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Abstract
We present a general Fourier-based method which provides an accurate prediction of the approximation error, when the derivative of a signal s(t) is continuously reconstructed from uniform point samples or generalized measurements on s. This formalism applies to a wide class of convolution-based techniques. It provides a key tool, the frequency error kernel, for designing computationally efficient reconstruction schemes which are near optimal in the least-squares sense.
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- Condat, Laurent
- Möller, Torsten
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Supplemental Material
Shortfacts
Category |
Journal Paper |
Divisions |
Visualization and Data Analysis |
Journal or Publication Title |
IEEE Transactions on Signal Processing |
ISSN |
1053-587X |
Page Range |
pp. 2965-2969 |
Number |
6 |
Volume |
59 |
Date |
June 2011 |
Official URL |
http://www.cs.sfu.ca/~torsten/Publications/Papers/... |
Export |
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