|
|
|
|
| LEADER |
02249nmm a2200349 u 4500 |
| 001 |
EB002203443 |
| 003 |
EBX01000000000000001340644 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
240502 ||| eng |
| 020 |
|
|
|a 9783031494833
|
| 100 |
1 |
|
|a Zhang, Zhihua
|
| 245 |
0 |
0 |
|a Frame Theory in Data Science
|h Elektronische Ressource
|c by Zhihua Zhang, Palle E. T. Jorgensen
|
| 250 |
|
|
|a 1st ed. 2024
|
| 260 |
|
|
|a Cham
|b Springer International Publishing
|c 2024, 2024
|
| 300 |
|
|
|a VIII, 255 p. 7 illus., 6 illus. in color
|b online resource
|
| 505 |
0 |
|
|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
|
| 653 |
|
|
|a Artificial intelligence / Data processing
|
| 653 |
|
|
|a Environment
|
| 653 |
|
|
|a Climate Change Ecology
|
| 653 |
|
|
|a Environmental Sciences
|
| 653 |
|
|
|a Bioclimatology
|
| 653 |
|
|
|a Mathematics
|
| 653 |
|
|
|a Data Science
|
| 700 |
1 |
|
|a Jorgensen, Palle E. T.
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development
|
| 028 |
5 |
0 |
|a 10.1007/978-3-031-49483-3
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-031-49483-3?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 005.7
|
| 520 |
|
|
|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.
|