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Related papers: On generalized Walsh bases

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The osp(1,2)-covariant Lagrangian quantization of irreducible gauge theories [hep-th/9712204] is generalized to L-stage reducible theories. The dependence of the generating functional of Green's functions on the choice of gauge in the…

High Energy Physics - Theory · Physics 2009-10-31 B. Geyer , P. M. Lavrov , D. M"ulsch

We study degenerate hypoelliptic Ornstein-Uhlenbeck operators in $L^2$ spaces with respect to invariant measures. The purpose of this article is to show how recent results on general quadratic operators apply to the study of degenerate…

Analysis of PDEs · Mathematics 2014-11-25 Michela Ottobre , Grigorios Pavliotis , Karel Pravda-Starov

We consider the defocusing nonlinear Schr\"odinger equation on $\mathbb{T}^2$ with Wick ordered power nonlinearity, and prove almost sure global well-posedness with respect to the associated Gibbs measure. The heart of the matter is the…

Analysis of PDEs · Mathematics 2024-04-19 Yu Deng , Andrea R. Nahmod , Haitian Yue

In this paper we consider a question on existence of double series by generalized Walsh system, which are universal in weighted $L_\mu^1[0,1]^2$ spaces. In particular, we construct a weighted function $\mu(x,y)$ and a double series by…

Functional Analysis · Mathematics 2014-07-08 S. A. Episkoposian

In the present paper authors introduce the L_n-integral transform and the inverse integral transform for n = 2^k, k=0,1,2,..., as a generalization of the classical Laplace transform and the inverse Laplace transform, respectively.…

Classical Analysis and ODEs · Mathematics 2014-03-11 Nese Dernek , Fatih Aylikci

Representations of the superalgebra $osp(2|2)$ and current superalgebra $osp(2|2)^{(1)}_k$ in the standard basis are investigated. All finite-dimensional typical and atypical representations of $osp(2|2)$ are constructed by the vector…

High Energy Physics - Theory · Physics 2009-11-10 Yao-Zhong Zhang

Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundational models for vision and language, pre-trained on extensive…

The study is devoted to the interpretation and wellposedness of the stochastic NLS model \begin{equation*} (\imath \partial_t-\Delta)u=|u|^2+\dot{B}, \quad u_0=0,\quad \quad t\in \mathbb{R}, \ x\in \mathbb{T}, \end{equation*} where…

Analysis of PDEs · Mathematics 2025-12-03 Aurélien Deya , Reika Fukuizumi , Laurent Thomann

The offset linear canonical transform (OLCT) provides a more general framework for a number of well known linear integral transforms in signal processing and optics, such as Fourier transform, fractional Fourier transform, linear canonical…

Signal Processing · Electrical Eng. & Systems 2018-06-08 Haiye Huo

In this paper, we study the spectrality and frame-spectrality of exponential systems of the type $E(\Lambda,\varphi) = \{e^{2\pi i \lambda\cdot\varphi(x)}: \lambda\in\Lambda\}$ where the phase function $\varphi$ is a Borel measurable which…

Functional Analysis · Mathematics 2020-07-09 Jean-Pierre Gabardo , Chun-Kit Lai , Vignon Oussa

This paper introduces a nonconvex approach for sparse signal recovery, proposing a novel model termed the $\tau_2$-model, which utilizes the squared $\ell_1/\ell_2$ norms for this purpose. Our model offers an advancement over the $\ell_0$…

Optimization and Control · Mathematics 2024-09-02 Jianqing Jia , Ashley Prater-Bennette , Lixin Shen , Erin E. Tripp

We study regular inclusions of finite-dimensional von Neumann algebras from a matrix-theoretic perspective. To this end, we introduce a new combinatorial invariant of an inclusion, called the normalizer matrix, which encodes the structure…

Operator Algebras · Mathematics 2026-02-18 Keshab Chandra Bakshi , Silambarasan C

The Ornstein-Uhlenbeck (OU) process describes the dynamics of Brownian particles in a confining harmonic potential, thereby constituting the paradigmatic model of overdamped, mean-reverting Langevin dynamics. Despite its widespread…

Statistical Mechanics · Physics 2024-05-16 Luca Cocconi , Henry Alston , Jacopo Romano , Thibault Bertrand

We prove that, for $p \in [1, \infty),$ and integers $d$ at least 2, the $L^p$ analog ${\mathcal{O}}_d^p$ of the Cuntz algebra ${\mathcal{O}}_d$ is a purely infinite simple amenable Banach algebra. The proof requires what we call the…

Functional Analysis · Mathematics 2013-09-17 N. Christopher Phillips

As a greedy algorithm to recover sparse signals from compressed measurements, orthogonal matching pursuit (OMP) algorithm has received much attention in recent years. In this paper, we introduce an extension of the OMP for pursuing…

Information Theory · Computer Science 2014-04-01 Jian Wang , Seokbeop Kwon , Byonghyo Shim

In this paper we fill a necessary gap in order to realize the explicit comparison between the Kaluza Klein spectra of supergravity compactified on AdS_4 x X^7 and superconformal field theories living on the world volume of M2-branes. On the…

High Energy Physics - Theory · Physics 2009-10-31 D. Fabbri , P. Fre` , L. Gualtieri , P. Termonia

A collection of orthonormal bases for a complex dXd Hilbert space is called mutually unbiased (MUB) if for any two vectors v and w from different bases the square of the inner product equals 1/d: |<v,w>| ^{2}=1/d. The MUB problem is to…

Quantum Physics · Physics 2007-05-23 Arthur O. Pittenger , Morton H. Rubin

The two-parametric quantum superalgebra $U_{pq}[gl(2/2)]$ and its representations are considered. All finite-dimensional irreducible representations of this quantum superalgebra can be constructed and classified into typical and nontypical…

Quantum Algebra · Mathematics 2008-11-26 Nguyen Anh Ky

We extend the convergence method introduced in our works [8]-[10] for almost sure global well-posedness of Gibbs measure evolutions of the nonlinear Schr\"odinger (NLS) and nonlinear wave (NLW) equations on the unit ball in R^d to the case…

Analysis of PDEs · Mathematics 2015-08-12 Jean Bourgain , Aynur Bulut

Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become the go-to methodology for tackling image restoration and…

Computer Vision and Pattern Recognition · Computer Science 2020-09-01 Junaid Malik , Serkan Kiranyaz , Moncef Gabbouj