Kernel-based Approximation Methods using MATLAB
Jul 2015 · Interdisciplinary Mathematical Sciences Book 19 · World Scientific Publishing Company
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536
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About this ebook
In an attempt to introduce application scientists and graduate students to the exciting topic of positive definite kernels and radial basis functions, this book presents modern theoretical results on kernel-based approximation methods and demonstrates their implementation in various settings. The authors explore the historical context of this fascinating topic and explain recent advances as strategies to address long-standing problems.
Examples are drawn from fields as diverse as function approximation, spatial statistics, boundary value problems, machine learning, surrogate modeling and finance. Researchers from those and other fields can recreate the results within using the documented MATLAB code, also available through the online library. This combination of a strong theoretical foundation and accessible experimentation empowers readers to use positive definite kernels on their own problems of interest.
In an attempt to introduce application scientists and graduate students to the exciting topic of positive definite kernels and radial basis functions, this book presents modern theoretical results on kernel-based approximation methods and demonstrates their implementation in various settings. The...
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About the author
Gregory Fasshauer (Illinois Institute of Technology, USA);Michael McCourt (University of Colorado Denver, USA)
Gregory Fasshauer (Illinois Institute of Technology, USA);Michael McCourt (University of Colorado Denver, USA)
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