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Tensor Computation for Seismic Data Processing Linking Theory and Practice - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: E-Books (https://softwarez.info/Forum-E-Books) +--- Thread: Tensor Computation for Seismic Data Processing Linking Theory and Practice (/Thread-Tensor-Computation-for-Seismic-Data-Processing-Linking-Theory-and-Practice--980052) |
Tensor Computation for Seismic Data Processing Linking Theory and Practice - ebooks1001 - 05-25-2025 ![]() Free Download Tensor Computation for Seismic Data Processing: Linking Theory and Practice (Earth Systems Data and Models) by Feng Qian, Shengli Pan, Gulan Zhang English | April 27, 2025 | ISBN: 3031788990 | 253 pages | EPUB | 102 Mb 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 data, and tensor computation can help prevent possible harm to the multi-dimensional geological structure of the subsurface that occurred in classical seismic data analysis. It delivers a wealth of theoretical, computational, technical, and experimental details, presenting an engineer's perspective on tensor computation and an extensive investigation of tensor-based seismic data analysis techniques. Embark on a transformative exploration of seismic data processing―unlock the potential of tensor computation and reshape your approach to high-dimensional geological structures. The discussion begins with foundational chapters, providing a solid background in both seismic data processing and tensor computation. The heart of the book lies in its seven chapters on tensor-based seismic data analysis methods. From structured low-tubal-rank tensor completion to cutting-edge techniques like tensor deep learning and tensor convolutional neural networks, each method is meticulously detailed. The superiority of tensor-based data analysis methods over traditional matrix-based data analysis approaches is substantiated through synthetic and real field examples, showcasing their prowess in handling high-dimensional modern seismic data. Notable chapters delve into seismic noise suppression, seismic data interpolation, and seismic data super-resolution using advanced tensor models. The final chapter provides a cohesive summary of the conclusion and future research directions, ensuring readers facilitate a thorough understanding of tensor computation applications in seismic data processing. The appendix includes a hatful of information on existing tensor computation software, enhancing the book's practical utility. Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live Links are Interchangeable - Single Extraction |