Wavelet Scattering
Libraries:
DSP System Toolbox /
Feature Extractors
Description
The Wavelet Scattering block creates a framework for wavelet time
scattering in the Simulink® environment. Use this block to derive low-variance features from real-valued
data and then use those features in machine learning and deep learning applications. The block
uses predefined wavelet filters to compute the scalogram and applies an averaging filter to
the scalogram for feature extraction. For more information, see Wavelet Scattering (Wavelet Toolbox). To perform wavelet
scattering in MATLAB®, use the waveletScattering
(Wavelet Toolbox) function.
The Wavelet Scattering block requires Wavelet Toolbox™.
Examples
Ports
Input
Output
Parameters
Block Characteristics
Data Types |
|
Direct Feedthrough |
|
Multidimensional Signals |
|
Variable-Size Signals |
|
Zero-Crossing Detection |
|
References
[1] Andén, Joakim, and Stéphane Mallat. “Deep Scattering Spectrum.” IEEE Transactions on Signal Processing 62, no. 16 (August 2014): 4114–28. https://doi.org/10.1109/TSP.2014.2326991.
[2] Mallat, Stéphane. “Group Invariant Scattering.” Communications on Pure and Applied Mathematics 65, no. 10 (October 2012): 1331–98. https://doi.org/10.1002/cpa.21413.
Extended Capabilities
Version History
Introduced in R2022b
See Also
Functions
waveletScattering
(Wavelet Toolbox)
Topics
- Wavelet Scattering (Wavelet Toolbox)
- Fault Detection Using Wavelet Scattering and Recurrent Deep Networks (Wavelet Toolbox)