Deep Learning For Time Series Data

版本 1.0.2 (1.9 MB) 作者: MathWorks Student Competitions Team
The examples showcase two ways of using deep learning for classifying time-series data, i.e. ECG data.
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更新时间 2020/11/23
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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

引用格式

MathWorks Student Competitions Team (2024). Deep Learning For Time Series Data (https://github.com/mathworks/deep-learning-for-time-series-data/releases/tag/v1.0.2), GitHub. 检索来源 .

MATLAB 版本兼容性
创建方式 R2020a
兼容 R2020a 到 R2020b 的版本
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版本 已发布 发行说明
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

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要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。