Gaussian Continuous Wavelet Transform (cwt - 'gauss1','gauss2')
20 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
I want to do the process describe:
"Firstly vertical accelerartion was integrated and then differentiated using a Gaussian CWT, where IC's (Inicial Contact) were identified as the times of the minima. The differentiated signal underwent a further CWT differentiation from which FC's (Final Contact) were identified as the times of the maxima."
Iknow that to the integrated i need to use in the function cumtrapz.m and to find the minimum or maximum peak i can use the function findpeaks.m. My problem is how i can do the differention of Gaussian CWT? in the options of the function cwt.m the option od 'gauss1' or 'gauss2' are not exsit anymore? -I'm use in matalb R2022a
Thank you
0 Kommentare
Antworten (1)
Naren
am 26 Apr. 2023
Hello Itai,
In MATLAB, you can use the cwtft function with the'morl' wavelet and the'scales' input parameter set to a vector of scales at which to compute the transform to differentiate a signal using a Gaussian Continuous Wavelet Transform (CWT).
Here is an example code snippet:
% Define input signal
t = linspace(0, 1, 1000);
x = sin(2*pi*10*t) + randn(size(t));
% Compute CWT using Morlet wavelet and scales from 1 to 100
scales = 1:100;
cwt = cwtft(x, 'wavelet', 'morl', 'scales', scales);
% Compute differentiation of CWT coefficients
dcwt = diff(abs(cwt.cfs), 1, 2);
% Find maxima and minima of differentiated coefficients
maxima = findpeaks(dcwt);
minima = findpeaks(-dcwt);
In this example, the input signal x is first defined as a noisy sinusoid. Then, using the'morl' wavelet and scales between 1 and 100, we compute the CWT of x. The cwt structure contains the derived CWT coefficients.
The differentiation of the CWT coefficients is then calculated using the diff function. The dcwt variable holds the differentiated coefficients that are produced.
The findpeaks function is then used to determine the maximum and minimum values of the differentiated coefficients. In order to locate the negative peaks, we use -dcwt for the minima.
It should be noted that the code in the preceding sentence presupposes that the input signal x has been integrated over time to determine the vertical acceleration. To identify ICs and FCs according to the procedure you supplied, the generated signal can be subjected to the CWT differentiation and peak detection procedures.
Hope this resolves your issue.
0 Kommentare
Siehe auch
Kategorien
Mehr zu Continuous Wavelet Transforms finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!