Howtosignalprocessing
- What is wavelet time scattering?
- What is wavelet scattering transform?
- Why do we use wavelet transform?
What is wavelet time scattering?
Wavelet time scattering yields representations insensitive to translations in the input signal without sacrificing class discriminability. You can use the representations as inputs to a classifier. You can specify the duration of translation invariance and the number of wavelet filters per octave.
What is wavelet scattering transform?
Wavelet scattering (or scatter transform) generates a representation that's invariant to data rotation/translation and stable to deformations of your data. Uninformative variations in your data are discarded — e.g. an audio sample time-shifted by various amounts.
Why do we use wavelet transform?
The key advantage of the Wavelet Transform compared to the Fourier Transform is the ability to extract both local spectral and temporal information. A practical application of the Wavelet Transform is analyzing ECG signals which contain periodic transient signals of interest.
