![]() ![]() NB: this code has only been tested against Matlab v7.5.0 and the above dependencies. It would would be unlikely to work well for the example data you posted a picture of. Wavelet Transform Modulus Maxima Calculator for Matlab (WTMMCalc). frequency resolution of the short-time Fourier transform that limit its application when your sampling rate is low compared to the frequency of the data. ![]() If A is a vector, then detrend subtracts the trend from the elements of A. You need to apply the Short-Time Fourier Transform, which is the FFT applied over sliding windows of the data to get a picture of frequency over time. Description example D detrend (A) removes the best straight-fit line from the data in A and returns the remaining data. Incidentally, the plain FFT won't work if applied to the entire length of a signal that is time varying - the FFT assumes a stationary (non-varying) signal. The core component of the algorithm involves sifting a function x(t) to obtain a new function Y(t): First find the local minima and maxima of x(t). Wavelet methods might be an alternative, but the output of the EMD is very easy to interpret visually. The empirical mode decomposition (EMD) algorithm decomposes a signal x(t) into intrinsic mode functions (IMFs) and a residual in an iterative process. Recovering EEG brain signals: Artifact suppression with wavelet enhanced. (that is, where the frequencies change with time). This code is for illustration of the method described in: N.P. What I think you really want to do is decompose the signal into components based on local time scale. There is no need for the input points or the output points to be evenly spaced. Smooth signals using Savitzky-Golay filters, moving averages, moving medians, linear regression, or quadratic regression. ![]() Remove unwanted spikes, trends, and outliers from a signal. See this similar question and add some code that does a linear interpolation between the local minima and maxima. Savitzky-Golay smoothing, median and Hampel filtering, detrending. In addition, we are also going to make use of three mother wavelets for the respective high frequency components. I think what your question is asking for is interpolation between the local minima and local maxima of a time series (what you call the "relative minimum and maximum values".) Such a function would be the Daubechies 4 wavelet, that will be applied with the aid of the modified discrete wavelet transformation technqiue. ![]()
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