Gravitational Wave Science with Machine Learning
This book highlights the state of the art of machine learning applied to the science of gravitational waves. The main topics of the book range from the search for astrophysical gravitational wave signals to noise suppression techniques and control systems using machine learning-based algorithms. Dur...
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| 企業作者: | |
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| 其他作者: | |
| 格式: | 電子 電子書 |
| 語言: | 英语 |
| 出版: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2025.
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| 版: | 1st ed. 2025. |
| 叢編: | Springer Series in Astrophysics and Cosmology,
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| 主題: | |
| 在線閱讀: | https://doi.org/10.1007/978-981-96-1737-1 |
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書本目錄:
- 1. Neural network time-series classifiers for gravitational-wave searches in single-detector periods
- 2. A simple self similarity-based unsupervised noise monitor for gravitational-wave detectors
- 3 Simulation of transient noise bursts in gravitational wave interferometers
- 4. Efficient ML Algorithms for Detecting Glitches and Data Patterns in LIGO Time Series
- 5. Denoising gravitational-wave signals from binary black holes with dilated convolutional autoencoder.