Results 51 to 60 of about 146 (128)
On Kantorovich variant of Brass-Stancu operators
In this study, we deal with Kantorovich-type generalization of the Brass-Stancu operators. For the sequence of these operators, we study Lp{L}^{p}-convergence and give some upper estimates for the Lp{L}^{p}-norm of the approximation error via first-order
Bodur Murat +2 more
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Approximation by weighted Durrmeyer-type max-product neural network operators
This paper introduces a class of weighted Durrmeyer-type max-product neural network operators, which generalize the Kantorovich variant by incorporating a flexible weight function.
Wu Yile, Yu Dansheng
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SPARSE APPROXIMATION AND RECOVERY BY GREEDY ALGORITHMS IN BANACH SPACES
We study sparse approximation by greedy algorithms. We prove the Lebesgue-type inequalities for the weak Chebyshev greedy algorithm (WCGA), a generalization of the weak orthogonal matching pursuit to the case of a Banach space.
V. N. TEMLYAKOV
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Approximation of complex q-Beta-Baskakov-Szász-Stancu operators in compact disk
The purpose this study is to present and investigate the qq-Beta-Baskakov-Szasz-Stancu operator. The operators are accompanied by Voronovskaja-type consequences, which include both an exact approximation order and a quantitative assessment, specifically ...
Cheregi Larisa, Mursaleen Mohammad
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Faster approximation to multivariate functions by combined Bernstein-Taylor operators
In this article, we incorporate multivariate Taylor polynomials into the definition of the Bernstein operators to get a faster approximation to multivariate functions by these combined operators.
Duman Oktay
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On the approximation of Kantorovich-type Szàsz-Charlier operators
In this study, we introduce the Kantorovich-type modified Szàsz-Charlier operators and examine their approximation properties within the framework of fractional modeling and control theory. These operators are defined using the Korovkin-type theorem, and
Karabıyık Ümit, Ayık Adem
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In this article, we express a numerical form of the convergence using the suitable modulus of smoothness for linear compositions of the Mellin convolution operators.
Ozsarac Firat
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On the power of adaption and randomization
We present bounds on the maximal gain of adaptive and randomized algorithms over nonadaptive, deterministic ones for approximating linear operators on convex sets. If the sets are additionally symmetric, then our results are optimal.
David Krieg, Erich Novak, Mario Ullrich
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Approximation results in Orlicz spaces by modified sampling Kantorovich operators
This paper deals with the modified sampling Kantorovich operators. We start by presenting the primary notations of Orlicz spaces and fundamental auxiliary results.
Turgay Metin
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Chlodowsky variant of Bernstein-type operators on the domain
In the present paper, we deal with Bernstein-Chlodowsky type operators for approximating functions on the domain. We first present Bernstein-Chlodowsky type operators in two variables and then we discuss some examples of these operators under a domain ...
Serenbay Sevilay Kırcı +1 more
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