Deep Learning-Driven Vector Acoustic Field Inversion (Paperback)

Language: English

Published by Scholars' Press, 2025

6209141501 / 9786209141508

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Paperback. This monograph presents a deep learning framework for seabed characterization by fusing vector acoustic field physics with neural networks. It introduces Stokes parameters from vector hydrophones as robust features for geoacoustic inversion, and develops specialized networks (BP, MTL-TCN, U-Net + ATT-BP) to estimate sediment parameters and extract dispersion curves. Validated in the Yellow Sea, the method achieves core-comparable accuracy in minutes, significantly outperforming traditional techniques in speed and robustness. The work highlights the synergy between physical principles and data-driven learning, offering a scalable solution for real-time seabed mapping and advancing autonomous ocean sensing. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9786209141508

Title
Deep Learning-Driven Vector Acoustic Field Inversion (Paperback)
Author
Xiaoman Li
Publisher
Scholars' Press
Publication year
2025
Condition
new
Binding
Paperback
Language
English
ISBN 10
6209141501
ISBN 13
9786209141508

CitiRetail

Stevenage, United Kingdom

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AbeBooks seller since June 29, 2022

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