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Related papers: Random Operator-Valued Frames in Hilbert Spaces

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The purpose of this paper is to propose a definition of continuous frames of rank n for Krein spaces and to study their basic properties. Similarly to the Hilbert space case, continuous frames are characterized by the analysis, the…

Functional Analysis · Mathematics 2021-03-24 Diego Carrillo , Kevin Esmeral , Elmar Wagner

Let $X$ be a (real or complex) rearrangement-in\-va\-riant function space on $\Om$ (where $\Om = [0,1]$ or $\Om \subseteq \bbN$) whose norm is not proportional to the $L_2$-norm. Let $H$ be a separable Hilbert space. We characterize…

Functional Analysis · Mathematics 2016-09-06 Beata Randrianantoanina

We initiate the study of random iteration of automorphisms of real and complex projective surfaces, or more generally compact K{\"a}hler surfaces, focusing on the fundamental problem of classification of stationary measures. We show that,…

Algebraic Geometry · Mathematics 2022-11-08 Serge Cantat , Romain Dujardin

Transfer operators such as the Perron--Frobenius or Koopman operator play an important role in the global analysis of complex dynamical systems. The eigenfunctions of these operators can be used to detect metastable sets, to project the…

Dynamical Systems · Mathematics 2019-12-02 Stefan Klus , Ingmar Schuster , Krikamol Muandet

It is now well known that sparse or compressible vectors can be stably recovered from their low-dimensional projection, provided the projection matrix satisfies a Restricted Isometry Property (RIP). We establish new implications of the RIP…

Functional Analysis · Mathematics 2012-11-09 Rémi Gribonval , Morten Nielsen

Let $H_m(\mathbb B)$ be the analytic functional Hilbert space on the unit ball $\mathbb B \subset \mathbb C^n$ with reproducing kernel $K_m(z,w) = (1 - \langle z,w \rangle)^{-m}$. Using algebraic operator identities we characterize those…

Functional Analysis · Mathematics 2018-01-24 Jörg Eschmeier , Sebastian Langendörfer

Reproducing kernel Hilbert spaces (RKHSs) play an important role in many statistics and machine learning applications ranging from support vector machines to Gaussian processes and kernel embeddings of distributions. Operators acting on…

Functional Analysis · Mathematics 2021-04-06 Mattes Mollenhauer , Ingmar Schuster , Stefan Klus , Christof Schütte

Projection operators arise naturally as one-particle density operators associated to Slater determinants in fields such as quantum mechanics and the study of determinantal processes. In the context of the semiclassical approximation of…

Mathematical Physics · Physics 2024-05-29 Laurent Lafleche

Given the joint distribution of two random variables $X,Y$ on some second countable locally compact Hausdorff space, we investigate the statistical approximation of the $L^2$-operator defined by $[Pf](x) := \mathbb{E}[ f(Y) \mid X = x ]$…

Statistics Theory · Mathematics 2023-08-08 Mattes Mollenhauer , Péter Koltai

We analyze the notion of reproducing pair of weakly measurable functions, which generalizes that of continuous frame. We show, in particular, that each reproducing pair generates two Hilbert spaces, conjugate dual to each other. Several…

Functional Analysis · Mathematics 2016-03-09 Jean-Pierre Antoine , Michael Speckbacher , Camillo Trapani

We calculate within a semiclassical approximation the autocorrelation function of cross sections. The starting point is the semiclassical expression for the diagonal matrix elements of an operator. For general operators with a smooth…

Chaotic Dynamics · Physics 2007-08-22 Bruno Eckhardt , Shmuel Fishman , Imre Varga

We study weighted composition operators on Hilbert spaces of analytic functions on the unit ball with kernels of the form $(1-<z,w>)^{-\gamma}$ for $\gamma>0$. We find necessary and sufficient conditions for the adjoint of a weighted…

Functional Analysis · Mathematics 2012-07-26 Trieu Le

In this paper, we characterize all closed linear operators in a separable Hilbert space which are unitarily equivalent to an integral bi-Carleman operator in $L_2(R)$ with bounded and arbitrarily smooth kernel on $R^2$. In addition, we give…

Spectral Theory · Mathematics 2007-05-23 Igor M. Novitskii

In big data analysis, a simple task such as linear regression can become very challenging as the variable dimension $p$ grows. As a result, variable screening is inevitable in many scientific studies. In recent years, randomized algorithms…

Methodology · Statistics 2019-02-13 Yu-Hsiang Cheng , Tzee-Ming Huang , Su-Yun Huang

We design a quasi-interpolation operator from the Sobolev space $H^1_0(\Omega)$ to its finite-dimensional finite element subspace formed by piecewise polynomials on a simplicial mesh with a computable approximation constant. The operator 1)…

Numerical Analysis · Mathematics 2025-07-17 T. Chaumont-Frelet , M. Vohralik

We analyze perturbations of the harmonic oscillator type operators in a Hilbert space H, i.e. of the self-adjoint operator with simple positive eigenvalues $\mu_k$ satisfying $\mu_{k+1}-\mu_k \geq \Delta >0$. Perturbations are considered in…

Spectral Theory · Mathematics 2023-08-24 Boris Mityagin , Petr Siegl

Recently the behavior of operator monotone functions on unbounded intervals with respect to the relation of strictly positivity has been investigated. In this paper we deeply study such behavior not only for operator monotone functions but…

Functional Analysis · Mathematics 2017-09-26 M. Fujii , M. S. Moslehian , H. Najafi , R. Nakamoto

We construct some separable infinite dimensional homogeneous Hilbertian operator spaces which generalize the row and column spaces R and C. We show that separable infinite-dimensional Hilbertian JC*-triples are completely isometric to an…

Operator Algebras · Mathematics 2012-06-05 Matthew Neal , Bernard Russo

The mechanism of describing quantum states by standard probability (tomographic one) instead of wave function or density matrix is elucidated. Quantum tomography is formulated in an abstract Hilbert space framework, by means of the identity…

Quantum Physics · Physics 2008-11-26 V. I. Man'ko , G. Marmo , A. Simoni , A. Stern , E. C. G. Sudarshan , F. Ventriglia

We define a stochastic variant of the proximal point algorithm in the general setting of nonlinear (separable) Hadamard spaces for approximating zeros of the mean of a stochastically perturbed monotone vector field and prove its convergence…

Optimization and Control · Mathematics 2025-10-14 Nicholas Pischke