Zhang Z. Frame Theory in Data Science 2024

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Zhang Z. Frame Theory in Data Science 2024 (Size: 2.46 MB)
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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.
Preface
Abstract Frames
Harmonic Frames
Polynomial Frames
Analytic Extension of Frames
Quasi-Orthogonal Frames
Affine Frames
Spectral Domain of Frames
Periodic Frames
Frame Spectral Energy Distribution
Sparse Frame-Polynomial Coupling Representation
Object-Oriented Frame Analysis
Frame Networks
Further Reading

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