This book presents a collection of high-quality papers in applied and numerical mathematics, as well as approximation theory, all closely related to Wolfgang Dahmen’s scientific contributions. Compiled in honor of his 75th birthday, the papers are written by leading experts and cover topics including nonlinear approximation theory, numerical analysis of partial differential equations, learning theory, and electron microscopy. A unifying theme throughout the collection is the emphasis on a solid mathematical foundation, which serves as the basis for the most efficient numerical algorithms used to simulate complex phenomena.
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Ronald DeVore is a pioneer in nonlinear approximation theory but his career touches upon many other areas of mathematics, including numerical analysis, signal/image processing, machine learning, compressed sensing and statistical estimation. He is The Walter E. Koss Professor of Mathematics at Texas A&M University. Among numerous awards, he was elected member of the American Academy of Arts and Sciences in 2001, the National Academy of Sciences in 2017, and a fellow of the American Mathematical Society in 2012. In 2006, he was a Plenary Lecturer at the International Congress of Mathematicians in Madrid. Ronald DeVore received honorary doctorates from RWTH Aachen in 2004 and the University of Paris Sorbonne in 2019.
Angela Kunoth works mainly in numerical analysis of partial differential equations and corresponding optimal control problems, employing multilevel and wavelet methods. Since 2013, she is the holder of a chair in applied mathematics at the University of Cologne. Angela Kunoth was Editor-in-Chief for the SIAM Journal on Numerical Analysis from 2016-2021 and elected SIAM fellow 2023.
This book presents a collection of high-quality papers in applied and numerical mathematics, as well as approximation theory, all closely related to Wolfgang Dahmen’s scientific contributions. Compiled in honor of his 75th birthday, the papers are written by leading experts and cover topics including nonlinear approximation theory, numerical analysis of partial differential equations, learning theory, and electron microscopy. A unifying theme throughout the collection is the emphasis on a solid mathematical foundation, which serves as the basis for the most efficient numerical algorithms used to simulate complex phenomena.
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