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240502 ||| eng |
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|a 9783031494833
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|a Zhang, Zhihua
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245 |
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|a Frame Theory in Data Science
|h Elektronische Ressource
|c by Zhihua Zhang, Palle E. T. Jorgensen
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250 |
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|a 1st ed. 2024
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260 |
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|a Cham
|b Springer International Publishing
|c 2024, 2024
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300 |
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|a VIII, 255 p. 7 illus., 6 illus. in color
|b online resource
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505 |
0 |
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|a 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
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653 |
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|a Artificial intelligence / Data processing
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653 |
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|a Environment
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653 |
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|a Climate Change Ecology
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653 |
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|a Environmental Sciences
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653 |
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|a Bioclimatology
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653 |
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|a Mathematics
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653 |
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|a Data Science
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700 |
1 |
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|a Jorgensen, Palle E. T.
|e [author]
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041 |
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7 |
|a eng
|2 ISO 639-2
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989 |
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|b Springer
|a Springer eBooks 2005-
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490 |
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|a Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development
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028 |
5 |
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|a 10.1007/978-3-031-49483-3
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856 |
4 |
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|u https://doi.org/10.1007/978-3-031-49483-3?nosfx=y
|x Verlag
|3 Volltext
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|a 005.7
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520 |
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|a 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.
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