English
Related papers

Related papers: Operator inequalities I. Models and ergodicity

200 papers

The study presents a vector-valued extension of the classical Mercer theorem within the framework of reproducing kernel Hilbert spaces defined over Kaplansky-Hilbert modules associated with the algebra of essentially bounded measurable…

Functional Analysis · Mathematics 2025-11-24 A. Arziev , K. Kudaybergenov. P. Orinbaev

The main goal of this article is to present new inequalities for the spectral geometric mean $A\natural_t B$ of two positive definite operators $A, B$ on a Hilbert space. The obtained results complement many known inequalities for the…

Functional Analysis · Mathematics 2023-06-21 Hamid Reza Moradi , Shigeru Furuichi , Mohammad Sababheh

We consider a class of Hilbert-Schmidt integral operators with an isotropic, stationary kernel acting on square integrable functions defined on flat tori. For any fixed kernel which is positive and decreasing, we show that among all…

Spectral Theory · Mathematics 2016-06-10 Braxton Osting , Jeremy L. Marzuola , Elena Cherkaev

We give a necessary and sufficient condition for an n-hypercontraction to be similar to the backward shift operator in a weighted Bergman space. This characterization serves as a generalization of the description given in the Hardy space…

Functional Analysis · Mathematics 2014-02-26 Ronald G. Douglas , Hyun-Kyoung Kwon , Sergei Treil

Continuity, compactness, the spectrum and ergodic properties of the differentiation operator are investigated, when it acts in the Fr\'echet space of all Dirichlet series that are uniformly convergent in all half-planes $\{s \in \mathbb{C}…

Functional Analysis · Mathematics 2020-03-12 José Bonet

We explore connections between von Neumann's mean ergodic theorem and concepts of model theory. As an application we present a proof Wiener's generalization of von Neumann's result in which the group acting on the Hilbert space…

Logic · Mathematics 2014-09-23 Eduardo Dueñez , José Iovino

In Bayesian multilevel models, the data are structured in interconnected groups, and their posteriors borrow information from one another due to prior dependence between latent parameters. However, little is known about the behaviour of the…

Statistics Theory · Mathematics 2025-09-25 Marta Catalano , Hugo Lavenant , Francesco Mascari

We obtain a necessary and sufficient condition for a weighted composition operator to be co-isometric on a general weighted Hardy space of analytic functions in the unit disk whose reproducing kernel has the usual natural form. This turns…

Complex Variables · Mathematics 2021-07-14 María J. Martín , Alejandro Mas , Dragan Vukotić

In this paper, the notion of operator means in the setting of JB-algebras is introduced and their properties are studied. Many identities and inequalities are established, most of them have origins from operators on Hilbert space but they…

Functional Analysis · Mathematics 2023-05-03 Shuzhou Wang , Zhenhua Wang

By the use of the celebrated Kato's inequality we obtain in this paper some new inequalities for trace class operators on a complex Hilbert space H. Natural applications for functions defined by power series of normal operators are given as…

Functional Analysis · Mathematics 2014-09-29 Silvestru Sever Dragomir

In this paper, Heisenberg-Pauli-Weyl-type uncertainty inequalities are obtained for a pair of positive-self adjoint operators on a Hilbert space, whose spectral projectors satisfy a ``balance condition'' involving certain operator norms.…

Functional Analysis · Mathematics 2013-03-08 Alessio Martini

Covering ill-posed problems with compact and non-compact operators regarding the degree of ill-posedness is a never ending story written by many authors in the inverse problems literature. This paper tries to add a new narrative and some…

Numerical Analysis · Mathematics 2024-11-27 Frank Werner , Bernd Hofmann

Devoted to multi-task learning and structured output learning, operator-valued kernels provide a flexible tool to build vector-valued functions in the context of Reproducing Kernel Hilbert Spaces. To scale up these methods, we extend the…

Machine Learning · Computer Science 2018-05-25 Romain Brault , Florence d'Alché-Buc , Markus Heinonen

Our main theorem is in the generality of the axioms of Hilbert space, and the theory of unbounded operators. Consider two Hilbert spaces such that their intersection contains a fixed vector space D. It is of interest to make a precise…

Functional Analysis · Mathematics 2017-01-19 Palle Jorgensen , Erin Pearse , Feng Tian

Some consequences of promoting the object of noncommutativity ${\mathbf \theta}^{ij}$ to an operator in Hilbert space are explored. Consequently, a consistent algebra involving the enlarged set of canonical operators is obtained, which…

High Energy Physics - Theory · Physics 2008-11-26 Ricardo Amorim

In this paper, we extend some significant Ky Fan type inequalities in a large setting to operators on Hilbert spaces and derive their equality conditions. Among other things, we prove that if $f:[0,\infty)\rightarrow[0,\infty)$ is an…

Functional Analysis · Mathematics 2021-07-23 S. Habibzadeh , J. Rooin , M. S. Moslehian

Recent decades have provided a host of examples and applications motivating the study of nonlocal differential operators. We discuss a class of such operators acting on bounded domains, focusing on those with integrable kernels having…

Analysis of PDEs · Mathematics 2024-08-29 Mikil Foss , Michael Pieper

In this paper, we give the Alzer inequality for Hilbert space operators as follows: Let $A, B$ be two selfadjoint operators on a Hilbert space $\mathcal H$ such that $0 < A, B \le \frac{1}{2}I$, where $I$ is identity operator on $\mathcal…

Functional Analysis · Mathematics 2018-06-29 Ali Morassaei , Farzollah Mirzapour

This paper presents a framework for computing random operator-valued feature maps for operator-valued positive definite kernels. This is a generalization of the random Fourier features for scalar-valued kernels to the operator-valued case.…

Machine Learning · Computer Science 2016-08-22 Ha Quang Minh

While machine learning can accurately model process systems, models for decision making should also be structurally simple and physically interpretable. In process control, for example, (nearly) linear models are favored than nonlinear…

Systems and Control · Electrical Eng. & Systems 2026-05-25 Wentao Tang