Harmonic analysis and applications
著者
書誌事項
Harmonic analysis and applications
（Springer optimization and its applications, 168）
Springer, c2021
- : hbk
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注記
Includes bibliographical references
内容説明・目次
内容説明
This edited volume presents state-of-the-art developments in various areas in which Harmonic Analysis is applied. Contributions cover a variety of different topics and problems treated such as structure and optimization in computational harmonic analysis, sampling and approximation in shift invariant subspaces of L2( ), optimal rank one matrix decomposition, the Riemann Hypothesis, large sets avoiding rough patterns, Hardy Littlewood series, Navier-Stokes equations, sleep dynamics exploration and automatic annotation by combining modern harmonic analysis tools, harmonic functions in slabs and half-spaces, Andoni -Krauthgamer -Razenshteyn characterization of sketchable norms fails for sketchable metrics, random matrix theory, multiplicative completion of redundant systems in Hilbert and Banach function spaces. Efforts have been made to ensure that the content of the book constitutes a valuable resource for graduate students as well as senior researchers working on Harmonic Analysis and its various interconnections with related areas.
目次
Sampling and Approximation in Shift Invariant subspaces of L2( ) (Atreas).- Optimal 1 rank one matrix decomposition (Balan).- An arithmetical function related to Baez-Duarte's criterion for the Riemann hypothesis (Balazard).- Large Sets Avoiding Rough Patterns (Zahl).- PDE methods in Random Matrix Theory (Hall).- Structure and optimisation in computational harmonic analysis - On key aspects in sparse regularisation (Hansen).- Reflections on a Theorem of Boas and Pollard (Heil).- The Andoni-Krauthgamer-Razenshteyn characterization of sketchable norms fails for sketchable metrics (Noar).- Degree of convergence of some operators ^ 1 (Mohapatra).- Real variable methods in harmonic analysis and Navier-Stokes equations (Lemarie-Rieusset).- Explore intrinsic geometry of sleep dynamics and predict sleep stage by unsupervised learning techniques (Wu).- Harmonic functions in slabs and half-spaces (Madych).
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