Search arXivSearch

arXiv · 1503.01745

Generalized Prolate Spheroidal Wave Functions: Spectral Analysis and Approximation of Almost Band-limited Functions

Abstract

In this work, we first give various explicit and local estimates of the eigenfunctions of a perturbed Jacobi differential operator. These eigenfunctions generalize the famous classical prolate spheroidal wave functions (PSWFs), founded in 1960's by D. Slepian and his co-authors and corresponding to the case $α=β=0.$ They also generalize the new PSWFs introduced and studied recently in \cite{Wang2}, denoted by GPSWFs and corresponding to the case $α=β> -1.$ The main content of this work is devoted to the previous interesting special case $α=β.$ In particular, we give further computational improvements, as well as some useful explicit and local estimates of the GPSWFs. More importantly, by using the concept of a restricted Paley-Wiener space, we relate the GPSWFs to the solutions of a generalized energy maximisation problem. As a consequence, many desirable spectral properties of the self-adjoint compact integral operator associated with the GPSWFs are deduced from the rich literature of the PSWFs. In particular, we show that the GPSWFs are well adapted for the spectral approximation of the classical $c-$band-limited as well as almost $c-$band-limited functions. Finally, we provide the reader with some numerical examples that illustrate the different results of this work.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Abderrazek Karoui, Ahmed Souabni. 2015-06-11. Generalized Prolate Spheroidal Wave Functions: Spectral Analysis and Approximation of Almost Band-limited Functions. https://doi.org/10.1007/s00041-015-9420-3

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Fragment-wise differentiable structures

The $p$-modulus of curves, test plans, upper gradients, charts, differentials, approximations in energy and density of directions are all concepts associated to the theory of Sobolev functions in metric measure spaces. The purpose of this paper is to give an analogous geometric and ``fragment-wise'' theory for Lipschitz functions and Weaver derivations, where $\infty$-modulus of curve fragments, $\ast$-upper gradients and Alberti representations play a central role. We give a new definition of fragment-wise charts and prove that they exists for spaces with finite Hausdorff dimension. We give a replacement for $p$-duality in terms of Alberti representations and $\infty$-modulus and present the theory of $\ast$-upper gradients. Further, we give new and sharper results for approximations of Lipschitz functions, which yields the density of directions. Our results are applicable to all complete and separable metric measure spaces. In the process, we show that there are strong parallels between the Sobolev and Lipschitz worlds.

math.CA

Tensor Derivatives, Unified Tensor-Form Differential Equations, and Model Reduction via Partial Tucker Decomposition

This paper develops a unified tensor calculus for matrix-valued functions and their derivatives, and leverages this framework to construct efficient model reduction techniques for high-dimensional tensor differential equations. We first establish a systematic theory of tensor differentiation, wherein the derivative of a matrix with respect to another matrix is represented as a fourth-order tensor. Building on this calculus, we recast linear ordinary differential equations (ODEs) and partial differential equations(PDEs) into a compact tensor-matrix form $\frac{dX}{dt} = \A\ast X$. The general solution is expressed as $X = \exp(t\A)\ast C$, extending the matrix exponential to the tensor setting. Conditions under which the solution admits this exponential form are characterized in terms of the commutativity of the associated matrix slices. We introduce the partial Tucker decomposition (parTuckerD) to address the computational challenges posed by high-order tensor systems. On a synthetic electronic health record (EHR) tensor, parTuckerD achieves a relative reconstruction error of $0.0992$ with a $136.3\times$ compression ratio, matching the accuracy of the full TuckerD while preserving patient-level similarity structure. The results demonstrate that the proposed tensor calculus and parTuckerD framework provide a principle and computationally efficient approach for analyzing and solving high-dimensional tensor differential equations arising in data-intensive applications.

math.CA

Distance preservers for Lobachevsky space

We obtain a complete description of the class of entrywise preservers of Lorentz-Gram matrices. This resolves, for the case of constant negative curvature, the classification of entrywise preservers obtained by Schoenberg in the zero-curvature (Euclidean) and constant-positive-curvature (spherical) settings. These preservers admit a Lévy--Khintchine-type representation and their asymptotic characteristics are related to Krein's classification of screw lines in Lobachevsky space. Connections with complete Nevanlinna--Pick kernels and Bochner subordination are also obtained.

math.CA