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The problem of approximating the discrete spectra of families of self-adjoint operators that are merely strongly continuous is addressed. It is well-known that the spectrum need not vary continuously (as a set) under strong perturbations.…

Spectral Theory · Mathematics 2016-03-08 Jonathan Ben-Artzi , Thomas Holding

We obtain a necessary and sufficient condition for the operator of integration to be bounded on $H^\infty$ in a simply connected domain. The main ingredient of the proof is a new result on uniform approximation of Bloch functions. This…

Complex Variables · Mathematics 2016-12-28 Wayne Smith , Dmitriy M. Stolyarov , Alexander Volberg

We consider the problem of finding optimally stable polynomial approximations to the exponential for application to one-step integration of initial value ordinary and partial differential equations. The objective is to find the largest…

Numerical Analysis · Mathematics 2013-01-10 David I. Ketcheson , Aron J. Ahmadia

We prove that the inverse of a positive-definite matrix can be approximated by a weighted-sum of a small number of matrix exponentials. Combining this with a previous result [OSV12], we establish an equivalence between matrix inversion and…

Data Structures and Algorithms · Computer Science 2016-08-23 Sushant Sachdeva , Nisheeth K. Vishnoi

Convolutional neural networks have been highly successful in image-based learning tasks due to their translation equivariance property. Recent work has generalized the traditional convolutional layer of a convolutional neural network to…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Monami Banerjee , Rudrasis Chakraborty , Jose Bouza , Baba C. Vemuri

For a fixed d-tuple $\alpha=(\alpha_1,...,\alpha_d)\in(-1,\infty)^d$, consider the product space $\mathbb{R}_+^d:=(0,\infty)^d$ equipped with Euclidean distance $\arrowvert \cdot \arrowvert$ and the measure…

Functional Analysis · Mathematics 2025-04-10 Longben Wei

In this paper, we introduce a method known as polynomial frame approximation for approximating smooth, multivariate functions defined on irregular domains in $d$ dimensions, where $d$ can be arbitrary. This method is simple, and relies only…

Numerical Analysis · Mathematics 2020-05-27 Ben Adcock , Daan Huybrechs

In this paper we propose an approximation method for high-dimensional $1$-periodic functions based on the multivariate ANOVA decomposition. We provide an analysis on the classical ANOVA decomposition on the torus and prove some important…

Numerical Analysis · Mathematics 2022-01-31 Daniel Potts , Michael Schmischke

We rigorously investigate the convergence of a new numerical method, recently proposed by the authors, to approximate the reproduction numbers of a large class of age-structured population models with finite age span. The method consists in…

Numerical Analysis · Mathematics 2024-09-04 Simone De Reggi , Francesca Scarabel , Rossana Vermiglio

We describe a general approach for computing generators for elimination ideals associated with matrix and hypermatrix spectral decomposition constraints. We derive from these generators iterative procedures for approximating the spectral…

Spectral Theory · Mathematics 2015-03-24 Edinah K. Gnang

Approximation properties of multivariate Kantorovich-Kotelnikov type operators generated by different band-limited functions are studied. In particular, a wide class of functions with discontinuous Fourier transform is considered. The…

Classical Analysis and ODEs · Mathematics 2018-11-20 Yu. Kolomoitsev , M. Skopina

This work proposes a low complexity nonlinearity model and develops adaptive algorithms over it. The model is based on the decomposable---or rank-one, in tensor language---Volterra kernels. It may also be described as a product of FIR…

Systems and Control · Computer Science 2016-10-25 Felipe C. Pinheiro , Cassio G. Lopes

We consider approximating analytic functions on the interval $[-1,1]$ from their values at a set of $m+1$ equispaced nodes. A result of Platte, Trefethen \& Kuijlaars states that fast and stable approximation from equispaced samples is…

Numerical Analysis · Mathematics 2022-03-08 Ben Adcock , Alexei Shadrin

The class of matrix optimization problems (MOPs) has been recognized in recent years to be a powerful tool by researchers far beyond the optimization community to model many important applications involving structured low rank matrices.…

Optimization and Control · Mathematics 2014-01-13 Chao Ding , Defeng Sun , Jie Sun , Kim-Chuan Toh

This paper deals with approximation of smooth convex functions $f$ on an interval by convex algebraic polynomials which interpolate $f$ at the endpoints of this interval. We call such estimates "interpolatory". One important corollary of…

Classical Analysis and ODEs · Mathematics 2020-04-21 K. A. Kopotun , D. Leviatan , I. Petrova , I. A. Shevchuk

We give an algorithm to compute $N$ steps of a convolution quadrature approximation to a continuous temporal convolution using only $O(N \log N)$ multiplications and $O(\log N)$ active memory. The method does not require evaluations of the…

Numerical Analysis · Mathematics 2011-11-10 Achim Schädle , María López-Fernández , Christian Lubich

We consider and analyze applying a spectral inverse iteration algorithm and its subspace iteration variant for computing eigenpairs of an elliptic operator with random coefficients. With these iterative algorithms the solution is sought…

Numerical Analysis · Computer Science 2017-06-16 Harri Hakula , Mikael Laaksonen

We study spectral properties of one-dimensional singular perturbations of an unbounded selfadjoint operator and give criteria for the possibility to remove the whole spectrum by a perturbation of this type. A counterpart of our results for…

Spectral Theory · Mathematics 2013-04-23 Anton D. Baranov , Dmitry V. Yakubovich

The second order hypergeometric q-difference operator is studied for the value c=-q. For certain parameter regimes the corresponding recurrence relation can be related to a symmetric operator on the Hilbert space l^2(Z). The operator has…

Classical Analysis and ODEs · Mathematics 2010-11-03 Erik Koelink

Operator convex functions defined on the positive half-line play a prominent role in the theory of quantum information, where they are used to define quantum $f$-divergences. Such functions admit integral representations in terms of…

Optimization and Control · Mathematics 2023-05-23 Oisín Faust , Hamza Fawzi