Hello Viewers, in this video, Continuous Wavelet Transform (CWT) and its applications are discussed. A brief theory of wavelet and CWT is presented. Also Python and MATLAB implementation is shown to compute continuous wavelet transform coefficients in the form beautiful Scalograms. These Scalograms are very important for study of CWT of 1-D signals, highlighting their properties such as frequency break, time discontinuity, burst etc. These Scalograms can also be used as image input to some deep neural network for 1D signals classification.
This video has following contents:
- Theory of Continuous Wavelet Transform(CWT).
- CWT Applications.
- CWT of 1-D signals using Python (Using PyWavelet).
- Python Code for CWT of simple signal and signal with discontinuity.
- CWT of 1-D signals using MATLAB (Older and newer functions support).
- MATLAB Code for CWT of simple signal and signal with discontinuity.
Important Links:
1. Introduction to wavelet transform and its Applications: Click Here
2. Wavelet Transform Analysis of 1D signals using Python: Click Here
PyWavelet Documentation:
https://pywavelets.readthedocs.io/en/latest/
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