Tensor Computation for Seismic Data Processing Linking Theory and Practice /
This book aims to provide a comprehensive understanding of tensor computation and its applications in seismic data analysis, exclusively catering to seasoned researchers, graduate students, and industrial engineers alike. Tensor emerges as a natural representation of multi-dimensional modern seismic...
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| Autori principali: | , , |
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| Ente Autore: | |
| Natura: | Elettronico eBook |
| Lingua: | inglese |
| Pubblicazione: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edizione: | 1st ed. 2025. |
| Serie: | Earth Systems Data and Models,
6 |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/978-3-031-78900-7 |
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Sommario:
- Introduction
- The Foundations of Tensor Computation
- Tensor Completion for Seismic Data Reconstruction
- Tensor Low Rank Approximation for Seismic Footprint Suppression
- Tensor Deep Learning for Seismic Data Interpolation
- Transform Based Tensor Deep Learning for Seismic Random Noise Attenuation
- Order 𝒑 Tensor Deep Learning for Seismic Data Denoising
- Robust Tensor Deep Learning for Seismic Erratic Noise Attenuation
- Tensor Dictionary Learning for Seismic Data Super Resolution
- Conclusion and Future Research Directions.