Time Series Anomaly Detection Using Signal Processing and Deep Learning
In this paper, we propose a two-step approach for time series anomaly detection that combines signal processing techniques with deep learning methods. In the first step, we apply a bandpass filter to the time series data to reduce noise and highlight relevant frequency components, which enhances the...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/11/6254 |
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