Deep Learning For Time Series Data
The examples showcase two ways of using deep learning for classifying time-series data, i.e. ECG data.
https://github.com/mathworks/deep-learning-for-time-series-data
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The examples showcase two ways of using deep learning for classifying time-series data, i.e. ECG data. The first way is using continuous wavelet transform and transfer learning, whereas the second way is using Wavelet Scattering and LSTMs. The explanations of the code are in Chinese. The used data set can be download on：https://github.com/mathworks/physionet_ECG_data/
The video series (in Chinese) on this topic can be found as follows:
https://www.mathworks.com/videos/series/deep-learning-for-time-series-data.html
Cite As
MathWorks Student Competitions Team (2026). Deep Learning For Time Series Data (https://github.com/mathworks/deep-learning-for-time-series-data/releases/tag/v1.0.2), GitHub. Retrieved .
General Information
- Version 1.0.2 (1.86 MB)
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View License on GitHub
MATLAB Release Compatibility
- Compatible with R2020a to R2020b
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.2 | See release notes for this release on GitHub: https://github.com/mathworks/deep-learning-for-time-series-data/releases/tag/v1.0.2 |
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| 1.0.1 | See release notes for this release on GitHub: https://github.com/mathworks/deep-learning-for-time-series-data/releases/tag/v1.0.1 |
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| 1.0 |
