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Smoothness and Function Spaces

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Modern Fourier Analysis

Part of the book series: Graduate Texts in Mathematics ((GTM,volume 250))

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Abstract

We embark on the study of smoothness with a quick examination of differentiability properties of functions. There are several ways to measure differentiability and numerous ways to quantify smoothness. In this chapter we measure smoothness using the Laplacian, which is easily related to the Fourier transform. This relation becomes the foundation of a very crucial and deep connection between smoothness and Littlewood–Paley theory.

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Notes

  1. 1.

    If v i ≠ 1, then v i is irrational. Let q k  ∈ Q such that \(q_{k} \rightarrow v_{i}\) as \(k \rightarrow \infty \). Then \(f(q_{k}) = q_{k} \rightarrow v_{i}\) as \(k \rightarrow \infty \) but \(f(v_{i}) = -1\neq v_{i}\); thus, f is discontinuous at v i and by linearity everywhere else.

  2. 2.

    We used that \(g(b) - g(a) =\int_{ 0}^{1}\nabla g\big((1 - t)a + tb\big) \cdot (b - a)\,dt = \nabla g\big((1 - t^{{\ast}})a + t^{{\ast}}b\big) \cdot (b - a)\) for all \(a,b \in \mathbf{R}^{n}\), for a \(\mathcal{C}^{1}\) function g on \(\mathbf{R}^{n}\) and some t ∈ (0, 1), depending on g,a,b.

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Grafakos, L. (2014). Smoothness and Function Spaces. In: Modern Fourier Analysis. Graduate Texts in Mathematics, vol 250. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1230-8_1

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