Spectral analysis is an important method by which the variation in a data set can be decomposed into waves of different frequencies. In the form of the power spectral density it is usually estimated directly from the data using the fast Fourier transform which often requires considerable pre-process
Spectral theory for the fractal Laplacian in the context of h-sets
✍ Scribed by António M. Caetano; Sofia Lopes
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 327 KB
- Volume
- 284
- Category
- Article
- ISSN
- 0025-584X
No coin nor oath required. For personal study only.
✦ Synopsis
An h-set is a nonempty compact subset of the Euclidean n-space which supports a finite Radon measure for which the measure of balls centered on the subset is essentially given by the image of their radius by a suitable function h. In most cases of interest such a subset has Lebesgue measure zero and has a fractal structure.
Let Ω be a bounded
where (-Δ) -1 is the inverse of the Dirichlet Laplacian in Ω and tr Γ is, say, a trace type operator. The operator B, acting in convenient function spaces in Ω, is studied. Estimations for the eigenvalues of B are presented, and generally shown to be dependent on h, and the smoothness of the associated eigenfunctions is discussed. Some results on Besov spaces of generalised smoothness on R n and on domains which were obtained in the course of this work are also presented, namely pointwise multipliers, the existence of a universal extension operator, interpolation with function parameter and mapping properties of the Dirichlet Laplacian.
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