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Fr. 215.00
Palle E T Jorgensen, Palle E. T. Jorgensen, Zhihua Zhang
Frame Theory in Data Science
English · Paperback / Softback
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Description
This book establishes brand-new frame theory and technical implementation in data science, with a special focus on spatial-scale feature extraction, network dynamics, object-oriented analysis, data-driven environmental prediction, and climate diagnosis. Given that data science is unanimously recognized as a core driver for achieving Sustainable Development Goals of the United Nations, these frame techniques bring fundamental changes to multi-channel data mining systems and support the development of digital Earth platforms. This book integrates the authors' frame research in the past twenty years and provides cutting-edge techniques and depth for scientists, professionals, and graduate students in data science, applied mathematics, environmental science, and geoscience.
List of contents
Abstract Frame Theory.- Fourier-type Frame Theory.- Bandlimited Framelet Theory.- Compactly Supported Framelet Theory.- Periodic Framelet Theory.- Spheroidal-type Frame Theory.- Big Data.- Climate Diagnosis.- Frame Neural Networks.
About the author
Product details
| Authors | Palle E T Jorgensen, Palle E. T. Jorgensen, Zhihua Zhang |
| Publisher | Springer, Berlin |
| Languages | English |
| Product format | Paperback / Softback |
| Released | 01.01.2025 |
| EAN | 9783031494857 |
| ISBN | 978-3-0-3149485-7 |
| No. of pages | 255 |
| Dimensions | 210 mm x 14 mm x 279 mm |
| Weight | 652 g |
| Illustrations | VIII, 255 p. 7 illus., 6 illus. in color. |
| Series |
Advances in Science, Technology & Innovation |
| Subject |
Natural sciences, medicine, IT, technology
> IT, data processing
> IT
|
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