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Derivatives of the noisy signal based on Gaussian wavelet

version 2.0.4 (2.82 KB) by Zhaoyi Yan
This code achieves n-th order derivatives of a noisy signal sampled at discrete time points.

15 Downloads

Updated 01 Dec 2021

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Calculating noisy signal derivatives is a highly ill problem. According to the algorithm proposed in this paper (ref: https://doi.org/10.1016/j.chemolab.2003.08.001 ), a wavelet-based method can be used to suppress the noise, which is the basis of the code. The requirement for the input data is
(1) time vector is monotonic;
(2) f value vector is periodic;
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Now, in version 2, the second requirement can be lifted up --- f can be non-periodic in essence.
Two examples are included in the zip file.

Cite As

Zhaoyi Yan (2022). Derivatives of the noisy signal based on Gaussian wavelet (https://www.mathworks.com/matlabcentral/fileexchange/102549-derivatives-of-the-noisy-signal-based-on-gaussian-wavelet), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2021b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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