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The main object of this paper is to construct a new genuine Bernstein-Durrmeyer type operators which have better features than the classical one. Some direct estimates for the modified genuine Bernstein-Durrmeyer operator by means of the…

Numerical Analysis · Mathematics 2018-10-17 Ana Maria Acu , P. N. Agrawal

In the present article, we deal with the overconvergence of the Sz?asz-Durrmeyer-Chlodowsky operators. Here we study the approximation properties e.g. upper estimates, Voronovskaja type result for these operators attached to analytic…

Classical Analysis and ODEs · Mathematics 2016-05-19 Meenu Goyal , P. N. Agrawal

In this paper, we introduce a Kantorovich type generalization of q-Bernstein-Stancu operators. We study the convergence of the introduced operators and also obtain the rate of convergence by these operators in terms of the modulus of…

Classical Analysis and ODEs · Mathematics 2015-05-27 M. Mursaleen , Khursheed J. Ansari , Asif Khan

This paper extends the algorithm schemes proposed in \cite{Nesterov2007a} and \cite{Nesterov2007b} to the minimization of the sum of a composite objective function and a convex function. Two proximal point-type schemes are provided and…

Optimization and Control · Mathematics 2011-05-03 Quoc Tran Dinh , Moritz Diehl

For analytic operator functions, we prove accumulation of branches of complex eigenvalues to the essential spectrum. Moreover, we show minimality and completeness of the corresponding system of eigenvectors and associated vectors. These…

Functional Analysis · Mathematics 2018-04-05 Christian Engström , Axel Torshage

The present paper concerns filtered de la Vall\'ee Poussin (VP) interpolation at the Chebyshev nodes of the four kinds. This approximation model is interesting for applications because it combines the advantages of the classical Lagrange…

Numerical Analysis · Mathematics 2021-01-13 D. Occorsio , W. Themistoclakis

In this article, we analyse the Kantorovich type exponential sampling operators and its linear combination. We derive the Voronovskaya type theorem and its quantitative estimates for these operators in terms of an appropriate K-functional.…

Functional Analysis · Mathematics 2020-02-10 B. Shivam , A. Sathish Kumar

Recent years have witnessed the introduction and development of extremely fast rational function algorithms. Many ideas in this realm arose from polynomial-based linear-algebraic algorithms. However, polynomial approximation is occasionally…

Numerical Analysis · Mathematics 2025-10-03 James Chok , Geoffrey M. Vasil

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 study approximation properties of general multivariate periodic quasi-interpolation operators, which are generated by distributions/functions $\widetilde{\varphi}_j$ and trigonometric polynomials $\varphi_j$. The class of such operators…

Classical Analysis and ODEs · Mathematics 2021-07-27 Yurii Kolomoitsev , Jürgen Prestin

Total variation (TV) is a widely used function for regularizing imaging inverse problems that is particularly appropriate for images whose underlying structure is piecewise constant. TV regularized optimization problems are typically solved…

Image and Video Processing · Electrical Eng. & Systems 2025-08-26 Edward P. Chandler , Shirin Shoushtari , Brendt Wohlberg , Ulugbek S. Kamilov

Our aim is to construct a finite automaton recognizing the set of words that are at a bounded distance from some word of a given regular language. We define new regular operators, the similarity operators, based on a generalization of the…

Formal Languages and Automata Theory · Computer Science 2012-06-27 Jean-Marc Champarnaud , Hadrien Jeanne , Ludovic Mignot

The proximity operator of a convex function is a natural extension of the notion of a projection operator onto a convex set. This tool, which plays a central role in the analysis and the numerical solution of convex optimization problems,…

Optimization and Control · Mathematics 2010-05-19 Patrick L. Combettes , Jean-Christophe Pesquet

We introduce an abstract neural flow framework for neural networks and neural operators. The framework contains two continuous-depth models, namely neural flows with composition and separation structures, and covers both finite-dimensional…

Machine Learning · Computer Science 2026-05-27 Shuang Chen , Juncai He , Xue-Cheng Tai

Neural operators serve as universal approximators for general continuous operators. In this paper, we derive the approximation rate of solution operators for the nonlinear parabolic partial differential equations (PDEs), contributing to the…

Machine Learning · Computer Science 2024-10-04 Takashi Furuya , Koichi Taniguchi , Satoshi Okuda

The problem of approximating the discrete spectra of families of self-adjoint operators that are merely strongly continuous is addressed. It is well-known that the spectrum need not vary continuously (as a set) under strong perturbations.…

Spectral Theory · Mathematics 2016-03-08 Jonathan Ben-Artzi , Thomas Holding

In this paper, we study a strong inverse approximation theorem and saturation order for the family of Kantorovich exponential sampling operators. The class of log-uniformly continuous and bounded functions, and class of log-H\"{o}lderian…

Functional Analysis · Mathematics 2023-10-11 Shivam Bajpeyi , A. Sathish Kumar , P. Devaraj

We investigate a class of composite nonconvex functions, where the outer function is the sum of univariate extended-real-valued convex functions and the inner function is the limit of difference-of-convex functions. A notable feature of…

Optimization and Control · Mathematics 2024-11-21 Hanyang Li , Ying Cui

Nikol'skii known theorem for the kernels satisfying a condition $A^*_n$, is proved and for kernels from wider class. Explicit formulas for calculating the value of an approximation of classes $\W^{r, \beta}_{p, n} $ by convolution operators…

Classical Analysis and ODEs · Mathematics 2010-03-26 Viktor P. Zastavnyi

We study the approximation of functions which are invariant with respect to certain permutations of the input indices using flow maps of dynamical systems. Such invariant functions includes the much studied translation-invariant ones…

Machine Learning · Computer Science 2022-08-19 Qianxiao Li , Ting Lin , Zuowei Shen