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The finite Legendre transform (fLT) for filtering and fitting of exponentials and other smooth functions

A method is introduced for effectively filtering or fitting noisy exponentials or other smooth experimental data.

The method consists of two steps: (1) The transform of the noisy signal from the time-domain (t-domain) into the Legendre-domain (L-domain) and (2a) reconstruction and effective noise removal using the lower Legendre components (filtering), or (2b) fitting of the lower Legendre components using a nonlinear least squares method to find the amplitudes and the decay times of noisy exponentials (fitting).

In this version (v1.2), we also release a pure-python solution to give a real platform independent support, in case the c/c++ library is not work.

Source code for fLTlib can be found at our web page.

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1.2

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1.0

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Filename, size & hash SHA256 hash help File type Python version Upload date
fLTlib_v1_2.tar.gz (275.0 kB) Copy SHA256 hash SHA256 Source None Aug 20, 2014

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