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
Vous suivez désormais cette soumission
- Les mises à jour seront visibles dans votre flux de contenu suivi
- Selon vos préférences en matière de communication il est possible que vous receviez des e-mails
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
Citation pour cette source
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. Extrait(e) le .
Informations générales
- Version 1.0.2 (1,86 Mo)
-
Afficher la licence sur GitHub
Compatibilité avec les versions de MATLAB
- Compatible avec les versions R2020a à R2020b
Plateformes compatibles
- Windows
- macOS
- Linux
| Version | Publié le | Notes de version | 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 |
||
| 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 |
||
| 1.0 |
