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The translation of an operator is defined by using conjugation with time-frequency shifts. Thus, one can define $\Lambda$-shift-invariant subspaces of Hilbert-Schmidt operators, finitely generated, with respect to a lattice $\Lambda$ in…

Functional Analysis · Mathematics 2021-04-19 Antonio G. García

This paper is concerned with the problem of sampling and interpolation involving derivatives in shift-invariant spaces and the error analysis of the derivative sampling expansions for fundamentally large classes of functions. A new type of…

Functional Analysis · Mathematics 2024-02-15 Kumari Priyanka , A. Antony Selvan

Sampling theory in spaces other than the space of band-limited functions has recently received considerable attention. This is in part because the band-limitedness assumption is not very realistic in many applications. In addition,…

Classical Analysis and ODEs · Mathematics 2007-05-23 Cristina Blanco , Carlos Cabrelli , Sigrid Heineken

In this article, we characterize reducing and invariant subspaces of the space of square integrable functions defined in the unit circle and having values in some Hardy space with multiplicity. We consider subspaces that reduce the…

Functional Analysis · Mathematics 2023-09-28 Alejandra Aguilera , Carlos Cabrelli , Diana Carbajal , Victoria Paternostro

We provide sufficient conditions on a family of functions $(\phi_\alpha)_{\alpha\in A}:\mathbb{R}^d\to\mathbb{R}$ for sampling of multivariate bandlimited functions at certain nonuniform sequences of points in $\mathbb{R}^d$. We consider…

Functional Analysis · Mathematics 2018-02-14 Keaton Hamm

We study the space spanned by the integer shifts of a bivariate Gaussian function and the problem of reconstructing any function in that space from samples scattered across the plane. We identify a large class of lattices, or more generally…

Functional Analysis · Mathematics 2024-08-07 José Luis Romero , Alexander Ulanovskii , Ilya Zlotnikov

The concept of translation of an operator allows to consider the analogous of shift-invariant subspaces in the class of Hilbert-Schmidt operators. Thus, we extend the concept of average sampling to this new setting, and we obtain the…

Functional Analysis · Mathematics 2021-01-25 Antonio G. García

The goal of the paper is to consider Bernstein-Mellin subspaces in the Lebesgue-Mellin spaces and establishing for functions in these subspaces new sampling theorems and Riesz-Boas high-order interpolation formulas.

Classical Analysis and ODEs · Mathematics 2021-11-30 Isaac Z. Pesenson

In this paper, an equivalence between existence of particular exponential Riesz bases for multivariate bandlimited functions and existence of certain polynomial interpolants for these bandlimited functions is given. For certain classes of…

Numerical Analysis · Mathematics 2010-09-13 B. A. Bailey

In this paper, we discuss to the nonuniform sampling problem in principal shift-invariant subspaces of mixed Lebesgue spaces. We proposed a fast reconstruction algorithm which allows to exactly reconstruct the functions in the principal…

Functional Analysis · Mathematics 2018-01-26 Qingyue Zhang

The Special Affine Fourier Transformation(SAFT), which generalizes several well-known unitary transformations, has been demonstrated as a valuable tool in signal processing and optics. In this paper, we explore the multivariate dynamical…

Functional Analysis · Mathematics 2024-09-16 Meng Ning , Li-Ping Wu , Qing-yue Zhang , Bei Liu

The use of unitary invariant subspaces of a Hilbert space $\mathcal{H}$ is nowadays a recognized fact in the treatment of sampling problems. Indeed, shift-invariant subspaces of $L^2(\mathbb{R})$ and also periodic extensions of finite…

Functional Analysis · Mathematics 2016-06-29 Antonio G. García , Alberto Ibort , María J. Muñoz-Bouzo

We introduce a sampling theoretic framework for the recovery of smooth surfaces and functions living on smooth surfaces from few samples. The proposed approach can be thought of as a nonlinear generalization of union of subspace models…

Signal Processing · Electrical Eng. & Systems 2019-03-05 Qing Zou , Mathews Jacob

The method of compatible sequences is introduced in order to produce non-trivial (closed) invariant subspaces of (bounded linear) operators. Also a topological tool is used which is new in the search of invariant subspaces: the extraction…

Functional Analysis · Mathematics 2007-05-23 George Androulakis

Generalized sampling consists in the recovery of a function $f$, from the samples of the responses of a collection of linear shift-invariant systems to the input $f$. The reconstructed function is typically a member of a finitely generated…

Numerical Analysis · Mathematics 2021-06-18 Alexis Goujon , Shayan Aziznejad , Alireza Naderi , Michael Unser

The structure of subspaces of a Hilbert space that are invariant under unitary representations of a discrete group is related to a notion of Hilbert modules endowed with inner products taking values in spaces of unbounded operators. A…

Functional Analysis · Mathematics 2015-07-01 Davide Barbieri , Eugenio Hernández , Victoria Paternostro

Let $\lambda$ be a positive number, and let $(x_j:j\in\mathbb Z)\subset\mathbb R$ be a fixed Riesz-basis sequence, namely, $(x_j)$ is strictly increasing, and the set of functions $\{\mathbb R\ni t\mapsto e^{ix_jt}:j\in\mathbb Z\}$ is a…

Classical Analysis and ODEs · Mathematics 2010-03-19 Th. Schlumprecht , N. Sivakumar

The Grassmannian model represents harmonic maps from Riemann surfaces by families of shift-invariant subspaces of a Hilbert space. We impose a natural symmetry condition on the shift-invariant subspaces that corresponds to considering an…

Functional Analysis · Mathematics 2019-12-06 Alexandru Aleman , Rui Pacheco , John C. Wood

This book deals with functions allowing to express the dissimilarity (discrepancy) between two data fields or ''divergence functions'' with the aim of applications to linear inverse problems. Most of the divergences found in the litterature…

Optimization and Control · Mathematics 2020-03-04 Henri Lantéri

It is often possible to perform reduced order modelling by specifying linear subspace which accurately captures the dynamics of the system. This approach becomes especially appealing when linear subspace explicitly depends on parameters of…

Machine Learning · Computer Science 2026-04-17 Vladimir Fanaskov , Vladislav Trifonov , Alexander Rudikov , Ekaterina Muravleva , Ivan Oseledets
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