Anomaly Detection in Fractal Time Series with LSTM Autoencoders
This study explores the application of neural networks for anomaly detection in time series data exhibiting fractal properties, with a particular focus on changes in the Hurst exponent. The objective is to investigate whether changes in fractal properties can be identified by transitioning from the...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
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Multidisciplinary Digital Publishing Institute
2024
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| Online Access: | https://hdl.handle.net/1721.1/157317 |