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We develop an approximation theory in Hilbert spaces that generalizes the classical theory of approximation by entire functions of exponential type. The results advance harmonic analysis on manifolds and graphs, thus facilitating data…

Functional Analysis · Mathematics 2014-03-07 Isaac Z. Pesenson , Meyer Z. Pesenson

The paper presents new and known results on estimates of important linear and nonlinear approximation characteristics of generalized Wiener classes of functions of several variables in different metrics.

Classical Analysis and ODEs · Mathematics 2026-01-06 Andrii Shidlich

In this paper we study best \(m\)-term trigonometric approximation in weighted Wiener spaces and its consequences for Besov and Sobolev spaces with bounded mixed derivative/difference. We obtain several sharp asymptotic bounds for weighted…

Functional Analysis · Mathematics 2025-11-21 Moritz Moeller , Serhii Stasyuk , Tino Ullrich

In this paper we reconsider the notion of an optimal effective Hamiltonian for the semiclassical propagation of the Wigner distribution in phase space. An explicit expression for the optimal effective Hamiltonian is obtained in the short…

Quantum Physics · Physics 2017-05-11 Dries Sels , Fons Brosens

For an arbitrary self-adjoint operator $B$ in a Hilbert space $H$, we present direct and inverse theorems establishing the relationship between the degree of smoothness of a vector $x \in H$ with respect to the operator $B$, the rate of…

Functional Analysis · Mathematics 2007-09-27 S. M. Torba , M. L. Gorbachuk , Ya. I. Grushka

Gaussian processes are a powerful class of non-linear models, but have limited applicability for larger datasets due to their high computational complexity. In such cases, approximate methods are required, for example, the recently…

Methodology · Statistics 2026-03-24 Soham Mukherjee , Manfred Claassen , Paul-Christian Bürkner

The necessary and sufficient conditions for existence of a generalized representer theorem are presented for learning Hilbert space-valued functions. Representer theorems involving explicit basis functions and Reproducing Kernels are a…

Machine Learning · Computer Science 2018-09-21 Sanket Diwale , Colin Jones

By making a seminal use of the maximum modulus principle of holomorphic functions we prove existence of $n$-best kernel approximation for a wide class of reproducing kernel Hilbert spaces of holomorphic functions in the unit disc, and for…

Complex Variables · Mathematics 2022-01-20 Tao Qian

The idea of best approximation in linear n-normed space is presented and some examples showing various possibilities of best approximations in linear n-normed space is given. Also, we study strictly convex n-norm and enquire about the…

Functional Analysis · Mathematics 2023-09-27 Prasenjit Ghosh , T. K. Samanta

We prove a "quantified" version of the Weyl-von Neumann theorem, more precisely, we estimate the ranks of approximants to compact operators appearing in the Voiculescu's theorem applied to commutative algebras. This allows considerable…

Functional Analysis · Mathematics 2010-05-24 Jan Spakula

In this paper we consider Lorentz space with a mixed norm of periodic functions of many variables. We obtain the exact estimation of the best M-term approximations of Nikol'ski's, Besov's classes in the Lorentz space with the mixed norm.

Classical Analysis and ODEs · Mathematics 2016-05-27 G. Akishev

We give a new proof of Fejes T\'oth's zone conjecture: for any sequence $v_1,v_2,...,v_n$ of unit vectors in a real Hilbert space $\mathcal{H}$, there exists a unit vector $v$ in $\mathcal{H}$ such that \begin{equation*} |\langle v_k,v…

Functional Analysis · Mathematics 2020-11-04 Oscar Ortega-Moreno

We develope a local theory for frames on finite dimensional Hilbert spaces. In particular, a bounded frame on a finite dimensional Hilbert space contains a subset which is a good Riesz basis for a percentage (arbitrarily close to one) of…

Functional Analysis · Mathematics 2007-05-23 Peter G. Casazza

With the use of tensor product of Hilbert space, and a diagonalization procedure from operator theory, we derive an approximation formula for a general class of stochastic integrals. Further we establish a generalized Fourier expansion for…

Mathematical Physics · Physics 2015-05-13 Palle E. T. Jorgensen , Myung-Sin Song

We study discrete-time $(m,n)$-multirate systems on separable Hilbert spaces, solving the problem of approximating such a system by one which has a shorter multirate period $(m/q,n/q)$, optimally in the Hilbert-Schmidt norm. We work in the…

Optimization and Control · Mathematics 2020-05-05 Mikael Kurula

In this paper, we consider a class of prescribed Weingarten curvature equations. Under some sufficient condition, we obtain an existence result by the standard degree theory based on the a prior estimates for the solutions to the prescribed…

Differential Geometry · Mathematics 2019-10-25 Li Chen , Agen Shang , Qiang Tu

In the framework of a real Hilbert space we consider the problem of approaching solutions to a class of hierarchical variational inequality problems, subsuming several other problem classes including certain mathematical programs under…

Optimization and Control · Mathematics 2026-01-27 Pavel Dvurechensky , Meggie Marschner , Shimrit Shtern , Mathias Staudigl

In the present paper, we use a generalised shift operator in order to define a generalised modulus of smoothness. By its means, we define generalised Lipschitz classes of functions, and we give their constructive characteristics.…

Functional Analysis · Mathematics 2014-01-28 Faton M. Berisha , Nimete Sh. Berisha

We consider the nearest-neighbor spacing distributions of mixed random matrix ensembles interpolating between different symmetry classes, or between integrable and non-integrable systems. We derive analytical formulas for the spacing…

Mathematical Physics · Physics 2012-08-22 Sebastian Schierenberg , Falk Bruckmann , Tilo Wettig

We study the problem of predicting the future, though only in the probabilistic sense of estimating a future state of a time-varying probability distribution. This is not only an interesting academic problem, but solving this extrapolation…

Machine Learning · Statistics 2014-11-21 Christoph H. Lampert
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