Derivatives of the noisy signal based on Gaussian wavelet
Version 4.0 (1.97 KB) by
Zhaoyi Yan
This code achieves n-th order derivatives of a noisy signal sampled at discrete time points.
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 time vector is monotonic;
Cite As
Zhaoyi Yan (2024). 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
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Version | Published | Release Notes | |
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4.0 | input f vector can be aperiodic. |
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3.0.4 | update: tinq input can be scalar or vector. Note that : faket and pvec should keep the same shape (column or row vector). |
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2.0.4 | Non-periodic signals are acceptable. |
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1.0.4 | fix some error |
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1.0.3 | modify some expressions. |
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1.0.2 | modify some expressions. |
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1.0.1 | Correct some error |
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1.0.0 |