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
이 제출물을 팔로우합니다
- 팔로우하는 게시물 피드에서 업데이트를 확인할 수 있습니다
- 정보 수신 기본 설정에 따라 이메일을 받을 수 있습니다
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
인용 양식
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. 검색 날짜: .
일반 정보
- 버전 1.0.2 (1.86 MB)
-
GitHub에서 라이선스 보기
MATLAB 릴리스 호환 정보
- R2020a에서 R2020b까지의 릴리스와 호환
플랫폼 호환성
- Windows
- macOS
- Linux
| 버전 | 퍼블리시됨 | 릴리스 정보 | 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 |
