• Title/Summary/Keyword: Approximation theorem

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On Approximation by Post-Widder and Stancu Operators Preserving x2

  • Rempulska, Lucyna;Skorupka, Mariola
    • Kyungpook Mathematical Journal
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    • v.49 no.1
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    • pp.57-65
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    • 2009
  • In the papers [5]-[7] was examined approximation of functions by the modified Sz$\'{a}$sz-Mrakyan operators and other positive linear operators preserving $e_2(x)=x^2$. In this paper we introduce the Post-Widder and Stancu operators preserving $x^2$ in polynomial weighted spaces. We show that these operators have better approximation properties than classical Post-Widder and Stancu operators.

CONVERGENCE THEOREMS ON VISCOSITY APPROXIMATION METHODS FOR FINITE NONEXPANSIVE MAPPINGS IN BANACH SPACES

  • Jung, Jong-Soo
    • The Pure and Applied Mathematics
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    • v.16 no.1
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    • pp.85-98
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    • 2009
  • Strong convergence theorems on viscosity approximation methods for finite nonexpansive mappings are established in Banach spaces. The main theorem generalize the corresponding result of Kim and Xu [10] to the viscosity approximation method for finite nonexpansive mappings in a reflexive Banach space having a uniformly Gateaux differentiable norm. Our results also improve the corresponding results of [7, 8, 19, 20].

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A Wong-Zakai Type Approximation for the Multiple Ito-Wiener Integral

  • Lee, Kyu-Seok;Kim, Yoon-Tae;Jeon, Jong-Woo
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.05a
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    • pp.55-60
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    • 2002
  • We present an extension of the Wong-Zakai type approximation theorem for a multiple stochastic integral. Using a piecewise linear approximation $W^{(n)}$ of a Wiener process W, we prove that the multiple integral processes {${\int}_{0}^{t}{\cdots}{\int}_{0}^{t}f(t_{1},{\cdots},t_{m})W^{(n)}(t_{1}){\cdots}W^{(n)}(t_{m}),t{\in}[0,T]$} where f is a given symmetric function in the space $C([0,T]^{m})$, converge to the multiple Stratonovich integral of f in the uniform $L^{2}$-sense.

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BILINEAR SYSTEMS CONTROLLER DESIGN WITH APPROXIMATION TECHNIQUES

  • Lee, Sang-Hyuk;Lee, Keonhee
    • Journal of the Chungcheong Mathematical Society
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    • v.18 no.1
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    • pp.101-116
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    • 2005
  • Using the iterative method, we derive an controller realization of the bilinear system, which is resulted from the system reformulation. We utilize Banach Fixed Point Theorem to support proposed controller, and the simulation results are also illustrated to verify usefulness of this technique.

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APPROXIMATION BY CONVOLUTION TYPE DELTA SEQUENCE IN HIGHER DIMENSION

  • Shim, Hong-Tae;Park, Chin-Hong
    • Journal of applied mathematics & informatics
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    • v.16 no.1_2
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    • pp.633-641
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    • 2004
  • In this paper we deal with functions in higher dimension. We provide several convergence theorem for approximation by convolution type delta sequence. We also give sufficient and necessary condition for Gibbs phenomenon to exist.

ON ALMOST DEFERRED WEIGHTED CONVERGENCE

  • M. AIYUB;SONALI SHARMA;KULDIP RAJ
    • Journal of applied mathematics & informatics
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    • v.42 no.2
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    • pp.245-256
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    • 2024
  • This article introduces the notion of almost deferred weighted convergence, statistical deferred weighted almost convergence and almost deferred weighted statistical convergence for real valued sequences. Further, with the aid of interesting examples, we investigated some relationships among our proposed methods. Moreover, we prove a new type of approximation theorem and demonstrated that our theorem effectively extends and improves most of the earlier existing results. Finally, we have presented an example which proves that our theorem is a stronger than its classical versions.

SIZE DISTRIBUTION OF ONE CONNECTED COMPONENT OF ELLIPTIC RANDOM FIELD

  • Alodat, M.T.
    • Journal of the Korean Statistical Society
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    • v.36 no.4
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    • pp.479-488
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    • 2007
  • The elliptic random field is an extension to the Gaussian random field. We proved a theorem which characterizes the elliptic random field. We proposed a heuristic approach to derive an approximation to the distribution of the size of one connected component of its excursion set above a high threshold. We used this approximation to approximate the distribution of the largest cluster size. We used simulation to compare the approximation with the exact distribution.

A STUDY OF SIMULTANEOUS APPROXIMATION BY NEURAL NETWORKS

  • Hahm, N.;Hong, B.I.
    • Journal of applied mathematics & informatics
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    • v.26 no.1_2
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    • pp.317-324
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    • 2008
  • This paper shows the degree of simultaneous neural network approximation for a target function in $C^r$[-1, 1] and its first derivative. We use the Jackson's theorem for differentiable functions to get a degree of approximation to a target function by algebraic polynomials and trigonometric polynomials. We also make use of the de La Vall$\grave{e}$e Poussin sum to get an approximation order by algebraic polynomials to the derivative of a target function. By showing that the divided difference with a generalized translation network can be arbitrarily closed to algebraic polynomials on [-1, 1], we obtain the degree of simultaneous approximation.

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APPROXIMATIONS OF SOLUTIONS FOR A NONLOCAL FRACTIONAL INTEGRO-DIFFERENTIAL EQUATION WITH DEVIATED ARGUMENT

  • CHADHA, ALKA;PANDEY, DWIJENDRA N.
    • Journal of applied mathematics & informatics
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    • v.33 no.5_6
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    • pp.699-721
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    • 2015
  • This paper investigates the existence of mild solution for a fractional integro-differential equations with a deviating argument and nonlocal initial condition in an arbitrary separable Hilbert space H via technique of approximations. We obtain an associated integral equation and then consider a sequence of approximate integral equations obtained by the projection of considered associated nonlocal fractional integral equation onto finite dimensional space. The existence and uniqueness of solutions to each approximate integral equation is obtained by virtue of the analytic semigroup theory via Banach fixed point theorem. Next we demonstrate the convergence of the solutions of the approximate integral equations to the solution of the associated integral equation. We consider the Faedo-Galerkin approximation of the solution and demonstrate some convergenceresults. An example is also given to illustrate the abstract theory.

Adaptive Neural Control for Output-Constrained Pure-Feedback Systems (출력 제약된 Pure-Feedback 시스템의 적응 신경망 제어)

  • Kim, Bong Su;Yoo, Sung Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.1
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    • pp.42-47
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    • 2014
  • This paper investigates an adaptive approximation design problem for the tracking control of output-constrained non-affine pure-feedback systems. To satisfy the desired performance without constraint violation, we employ a barrier Lyapunov function which grows to infinity whenever its argument approaches some limits. The main difficulty in dealing with pure-feedback systems considering output constraints is that the system has a non-affine appearance of the constrained variable to be used as a virtual control. To overcome this difficulty, the implicit function theorem and mean value theorem are exploited to assert the existence of the desired virtual and actual controls. The function approximation technique based on adaptive neural networks is used to estimate the desired control inputs. It is shown that all signals in the closed-loop system are uniformly ultimately bounded.