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Quantitative Error Analysis for the Reconstruction of Derivatives

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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Authors
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Supplemental Material
Citation
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/...
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