Wavelets and their use in data analytics

In this complimentary webinar we take a look at how wavelet analysis is accessible in the SIMCA software. We provide a brief introduction to how we use wavelet analysis in data analytics. Wavelets look like small oscillating waves, and they have the capability of probing a signal according to scale, that is, bandpass of frequencies. The characteristic features of this approach are good compression and de-noising of complicated signals. The wavelet transform uses a mother wavelet, that is, a basis function, with a certain scale (width of the analyzing function window) to investigate the time-scale properties of an incoming signal. By varying the width of this window, both sharp and coarse properties of the signal are captured. A narrow wavelet is used for detecting the sharp features, and a wider wavelet is useful for uncovering general signal properties.

Topics for this webinar:

- Introduction to wavelet analysis
- Implementation in the SIMCA software
- Use of wavelets in signal compression
- Use of wavelets in signal de-noising
- Other uses of wavelet analysis