• Title/Summary/Keyword: Space Convergence

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WEAK AND STRONG CONVERGENCE OF THREE-STEP ITERATIONS WITH ERRORS FOR TWO ASYMPTOTICALLY NONEXPANSIVE MAPPINGS

  • Jeong, Jae-Ug
    • Journal of applied mathematics & informatics
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    • v.26 no.1_2
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    • pp.325-336
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    • 2008
  • In this paper, we prove the weak and strong convergence of the three-step iterative scheme with errors to a common fixed point for two asymptotically nonexpansive mappings in a uniformly convex Banach space under a condition weaker than compactness. Our theorems improve and generalize some previous results.

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SOME RESULTS ON p-DISTANCE AND SEQUENCE OF COMPLEX UNCERTAIN VARIABLES

  • Roy, Santanu;Saha, Sangeeta;Tripathy, Binod Chandra
    • Communications of the Korean Mathematical Society
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    • v.35 no.3
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    • pp.907-916
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    • 2020
  • In this paper, we introduce the notion of p-distance in a complex uncertain sequence space. By using the concepts of p-distance, we give some theorems of convergence. Also, in a complex uncertain sequence space, we develope some properties on convergence in measure.

Some properties of the convergence of sequences of fuzzy points in a fuzzy normed linear space

  • Rhie, Gil-Seob;Do, Young-Uk
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.143-147
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    • 2007
  • With a new ordinary norm as an analogy of Krishna and Sarma[5] and Bag and Samanta[1], we will characterize the notions of the convergence of the sequences of fuzzy points, the fuzzy, ${\alpha}$-Cauchy sequence and fuzzy completeness.

A STRONGLY CONVERGENT PARALLEL PROJECTION ALGORITHM FOR CONVEX FEASIBILITY PROBLEM

  • Dang, Ya-Zheng;Gao, Yan
    • Journal of applied mathematics & informatics
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    • v.30 no.1_2
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    • pp.93-100
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    • 2012
  • In this paper, we present a strongly convergent parallel projection algorithm by introducing some parameter sequences for convex feasibility problem. To prove the strong convergence in a simple way, we transmit the parallel algorithm in the original space to an alternating one in a newly constructed product space. Thus, the strong convergence of the parallel projection algorithm is derived with the help of the alternating one under some parametric controlling conditions.

ON COMPLETE CONVERGENCE FOR EXTENDED INDEPENDENT RANDOM VARIABLES UNDER SUB-LINEAR EXPECTATIONS

  • Deng, Xin;Wang, Xuejun
    • Journal of the Korean Mathematical Society
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    • v.57 no.3
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    • pp.553-570
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    • 2020
  • In this paper, we establish complete convergence for sequences of extended independent random variables and arrays of rowwise extended independent random variables under sub-linear expectations in Peng's framework. The results obtained in this paper extend the corresponding ones of Baum and Katz [1] and Hu and Taylor [11] from classical probability space to sub-linear expectation space.

ON THE CONVERGENCE OF NEWTON'S METHOD AND LOCALLY HOLDERIAN INVERSES OF OPERATORS

  • Argyros, Ioannis K.
    • The Pure and Applied Mathematics
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    • v.16 no.1
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    • pp.13-18
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    • 2009
  • A semilocal convergence analysis is provided for Newton's method in a Banach space. The inverses of the operators involved are only locally $H{\ddot{o}}lderian$. We make use of a point-based approximation and center-$H{\ddot{o}}lderian$ hypotheses for the inverses of the operators involved. Such an approach can be used to approximate solutions of equations involving nonsmooth operators.

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ON THE SOLUTION OF NONLINEAR EQUATIONS CONTAINING A NON-DIFFERENTIABLE TERM

  • Argyros, Ioannis K.
    • East Asian mathematical journal
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    • v.24 no.3
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    • pp.295-304
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    • 2008
  • We approximate a locally unique solution of a nonlinear operator equation containing a non-differentiable operator in a Banach space setting using Newton's method. Sufficient conditions for the semilocal convergence of Newton's method in this case have been given by several authors using mainly increasing sequences [1]-[6]. Here, we use center as well as Lipschitz conditions and decreasing majorizing sequences to obtain new sufficient convergence conditions weaker than before in many interesting cases. Numerical examples where our results apply to solve equations but earlier ones cannot [2], [5], [6] are also provided in this study.

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