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This paper extends the Concentration-Compactness Principle to Musielak-Orlicz spaces, working in both bounded and unbounded domains. We show that our results include important special cases like classical Orlicz spaces, variable exponent…

Analysis of PDEs · Mathematics 2025-09-16 Ala Eddine Bahrouni , Anouar Bahrouni

We review a new formalism based on Orlicz spaces for the description of large regular statistical systems. Our presentation includes both classical and quantum systems. The presented approach has the advantage that statistical mechanics is…

Mathematical Physics · Physics 2015-02-23 W. A. Majewski , L. E. Labuschagne

We characterize norm one complemented subspaces of Orlicz sequence spaces $\ell_M$ equipped with either Luxemburg or Orlicz norm, provided that the Orlicz function $M$ is sufficiently smooth and sufficiently different from the square…

Functional Analysis · Mathematics 2007-05-23 Beata Randrianantoanina

We obtain new sampling discretization results in Orlicz norms on finite dimensional spaces. As applications, we study sampling recovery problems, where the error of the recovery process is calculated with respect to different Orlicz norms.…

Functional Analysis · Mathematics 2024-08-27 Egor Kosov , Sergey Tikhonov

The concept of mixed norm spaces has emerged as a significant interest in fields such as harmonic analysis. In addition, the problem of function approximation through sampling series has been particularly noteworthy in the realm of…

Functional Analysis · Mathematics 2025-07-24 Priyanka Majethiya , Shivam Bajpeyi , Dhiraj Patel

In this paper, we provide a unifying theory concerning the convergence properties of the so-called max-product Kantorovich sampling operators based upon generalized kernels in the setting of Orlicz spaces. The approximation of functions…

Functional Analysis · Mathematics 2025-02-25 Lorenzo Boccali , Danilo Costarelli , Gianluca Vinti

In the paper we introduce Orlicz type functional spaces defined in terms of nonlocal convolution type integral functionals and study the main properties of these spaces. We show in particular that, under natural convexity and growth…

Functional Analysis · Mathematics 2026-03-03 Denis Borisov , Andrey Piatnitski

Employing the Orlicz functions we extend the Buzano's inequality which is a refinement of the Cauchy-Schwarz inequality. Also using the Orlicz functions we obtain several numerical radius inequalities for a bounded linear operator as well…

Functional Analysis · Mathematics 2024-08-26 Pintu Bhunia , Raj Kumar Nayak

The aim of this paper is to discuss the characterizations of the composition operators on Orlicz-Lorentz space to have finite ascent (or descent).

Functional Analysis · Mathematics 2023-07-24 Neha Bhatia , Anuradha Gupta

We prove uniform estimates for the expected value of averages of order statistics of bivariate functions in terms of their largest values by a direct analysis. As an application, uniform estimates for the expected value of averages of order…

Probability · Mathematics 2018-10-03 Richard Lechner , Markus Passenbrunner , Joscha Prochno

The optimal Orlicz target space is exhibited for embeddings of fractional-order Orlicz-Sobolev spaces in $\mathbb R^n$. An improved embedding with an Orlicz-Lorentz target space, which is optimal in the broader class of all…

Functional Analysis · Mathematics 2020-01-17 Angela Alberico , Andrea Cianchi , Luboš Pick , Lenka Slavíková

In this article we investigate the Fourier series and transforms for the functions defined on the [-pi, pi]^ d or on the R^d and belonging to the (Bilateral) Grand Lebesgue Spaces. As a particular case we obtain some results about Fourier's…

Functional Analysis · Mathematics 2010-10-22 E. Ostrovsky , L. Sirota

In this paper, based on concepts of convex sets and convex functions, we introduce new concepts of functions, Young functions, strong Young functions and Orlicz functions by relaxing definitions of functions, Young functions, strong Young…

Functional Analysis · Mathematics 2019-12-13 Abdulhameed Qahtan Abbood Altai , Nada Mohammed Abbas Alsafar

In this paper we show that, using combinatorial inequalities and Matrix-Averages, we can generate Musielak-Orlicz spaces, i.e., we prove that $1/\pi \sum_{\pi} \max\limits_{1 \leq i \leq n} \abs{x_i y_{i\pi(i)}} \sim \norm{x}_{\Sigma M_i}$,…

Functional Analysis · Mathematics 2012-08-09 Joscha Prochno

This thesis explores two important areas in the mathematical analysis of nonlinear partial differential equations: Generalized gradient flows and vector valued Orlicz spaces. The first part deals with the existence of strong solutions for…

Analysis of PDEs · Mathematics 2024-02-01 Thomas Ruf

In this paper, the concept of Musielak N-functions and Musielak-Orlicz spaces generated by them well be introduced. Facts and results of the measure theory will be applied to consider properties, calculus and basic approximation of Musielak…

Functional Analysis · Mathematics 2018-06-20 Abdulhameed Qahtan Abbood Altai

We study the expected value of support functions of random polytopes in a certain direction, where the random polytope is given by independent random vectors uniformly distributed in an isotropic convex body. All results are obtained by an…

Functional Analysis · Mathematics 2012-05-10 David Alonso-Gutierrez , Joscha Prochno

We give sufficient conditions for the continuity in norm of the translation operator in the Musielak-Orlicz LM spaces. An application to the convergence in norm of approximate identities is given, whereby we prove density results of the…

Functional Analysis · Mathematics 2017-10-25 Ahmed Youssfi , Youssef Ahmida

We study extension theorems for Lipschitz-type operators acting on metric spaces and with values on spaces of integrable functions. Pointwise domination is not a natural feature of such spaces, and so almost everywhere inequalities and…

Functional Analysis · Mathematics 2019-10-02 W. V. Cavalcante , P. Rueda , E. A. Sánchez-Pérez

Transcendental functions, such as exponentials and logarithms, appear in a broad array of computational domains: from simulations in curvilinear coordinates, to interpolation, to machine learning. Unfortunately they are typically expensive…

Computational Physics · Physics 2022-06-22 Jonah M. Miller , Joshua C. Dolence , Daniel Holladay