Spectral Theory of the Weighted Fourier Transform with respect to a Function in $\mathbb{R}^n$: Uncertainty Principle and Diffusion-Wave Applications
Gustavo Dorrego, Luciano Luque

TL;DR
This paper extends the weighted Fourier transform to n-dimensional space, develops a spectral theory, and applies it to fractional diffusion-wave equations, revealing new uncertainty principles and explicit solutions involving Fox H-functions.
Contribution
It introduces a generalized spectral framework for the weighted Fourier transform in multiple dimensions and applies it to fractional PDEs, establishing new theoretical and practical tools.
Findings
Established a spectral theory including Plancherel and inversion formulas.
Derived a Heisenberg-type uncertainty principle depending on geometric deformation.
Explicitly expressed solutions of fractional diffusion-wave equations using Fox H-functions.
Abstract
In this paper, we generalize the weighted Fourier transform with respect to a function, originally proposed for the one-dimensional case in \cite{Dorrego}, to the -dimensional Euclidean space . We develop a comprehensive spectral theory on a weighted Hilbert space, establishing the Plancherel identity, the inversion formula, the convolution theorem, and a Heisenberg-type uncertainty principle depending on the geometric deformation. Furthermore, we utilize this framework to rigorously define the weighted fractional Laplacian with respect to a function, denoted by . Finally, we apply these tools to solve the generalized time-space fractional diffusion-wave equation, demonstrating that the fundamental solution can be expressed in terms of the Fox H-function, intrinsically related to the generalized -Mellin transform introduced in…
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Taxonomy
TopicsMathematical Analysis and Transform Methods · Fractional Differential Equations Solutions · Image and Signal Denoising Methods
