From the course: Wavelet Analysis: Applications with Wolfram Language
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Frequency Detection in a Time Series - Wolfram Language Tutorial
From the course: Wavelet Analysis: Applications with Wolfram Language
Frequency Detection in a Time Series
So let us now look at certain examples associated with using wavelet analysis. The first one is associated with detecting frequency in a time series using wavelet analysis. Recall that the traditional method that we tend to make use of is Fourier transform, but we are going to show you in this example how you could relate what you see in the wavelet domain to a certain frequency. So as an example, let us start with a single frequency example wherein we are going to take a function. It's a cos(2π) frequency. And we are going to vary the frequency. We'll put all of this inside of a manipulate. We are going to perform a ContinuousWaveletTransform. We are going to make use of the GaborWavelet of order 6. We are going to do a decomposition that consists of eight octaves and four voices. When I evaluate this, you get a manipulate that looks as follows. This is the signal that we are doing the decomposition on, and it consists of a certain frequency, in this case 10 hertz. And you can see…
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