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
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
引用格式
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. 检索时间: .
一般信息
- 版本 1.0.2 (1.9 MB)
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在 GitHub 上查看许可证
MATLAB 版本兼容性
- 兼容 R2020a 到 R2020b 的版本
平台兼容性
- Windows
- macOS
- Linux
| 版本 | 已发布 | 发行说明 | 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 |
