• 제목/요약/키워드: Weak convergence.

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대칭확률변수(對稱確率變數)의 대수(對數)의 법칙(法則)에 대하여 (On the Weak Law of Large Numbers for the Sums of Sign-Invariant Random Variables)

  • 홍덕헌
    • Journal of the Korean Data and Information Science Society
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    • 제4권
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    • pp.53-63
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    • 1993
  • We consider various types of weak convergence for sums of sign-invariant random variables. Some results show a similarity between independence and sign-invariance. As a special case, we obtain a result which strengthens a weak law proved by Rosalsky and Teicher [6] in that some assumptions are deleted.

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대기네트웤에 있어서 대기자수와 대기시간사이의 관계 (RELATIONSHIP BETWEEN QUEUE LENGTHS AND WAITING TIMES FOR QUEUEING NETWORK MODELS)

  • 홍성조
    • 대한산업공학회지
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    • 제20권3호
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    • pp.139-149
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    • 1994
  • For general open queueing network models, the relationship between weak limits of queue lengths and waiting times at stations is investigated under heavy traffic situations. It is shown that under suitable normalization, weak convergence of queue lengths and arrival processes is a sufficient condition for that of waiting times, and is also necessary condition when the network is of feedforward type. Moreover, these weak limits for queue lengths and waiting times are shown to be simply related.

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ON THE WEAK LAW FOR RANDOMLY INDEXED PARTIAL SUMS FOR ARRAYS

  • Hong, Dug-Hun;Sung, Soo-Hak;Andrei I.Volodin
    • 대한수학회논문집
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    • 제16권2호
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    • pp.291-296
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    • 2001
  • For randomly indexed sums of the form (Equation. See Full-text), where {X(sub)ni, i$\geq$1, n$\geq$1} are random variables, {N(sub)n, n$\geq$1} are suitable conditional expectations and {b(sub)n, n$\geq$1} are positive constants, we establish a general weak law of large numbers. Our result improves that of Hong [3].

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COMMON FIXED POINTS OF TWO NONEXPANSIVE MAPPINGS BY A MODIFIED FASTER ITERATION SCHEME

  • Khan, Safeer Hussain;Kim, Jong-Kyu
    • 대한수학회보
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    • 제47권5호
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    • pp.973-985
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    • 2010
  • We introduce an iteration scheme for approximating common fixed points of two mappings. On one hand, it extends a scheme due to Agarwal et al. [2] to the case of two mappings while on the other hand, it is faster than both the Ishikawa type scheme and the one studied by Yao and Chen [18] for the purpose in some sense. Using this scheme, we prove some weak and strong convergence results for approximating common fixed points of two nonexpansive self mappings. We also outline the proofs of these results to the case of nonexpansive nonself mappings.

APPROXIMATING COMMON FIXED POINTS OF ONE-STEP ITERATIVE SCHEME WITH ERROR FOR NON-SELF ASYMPTOTICALLY NONEXPANSIVE IN THE INTERMEDIATE SENSE MAPPINGS

  • Saluja, Gurucharan Singh;Nashine, Hemant Kumar
    • East Asian mathematical journal
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    • 제26권3호
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    • pp.429-440
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    • 2010
  • In this paper, we study a new one-step iterative scheme with error for approximating common fixed points of non-self asymptotically nonexpansive in the intermediate sense mappings in uniformly convex Banach spaces. Also we have proved weak and strong convergence theorems for above said scheme. The results obtained in this paper extend and improve the recent ones, announced by Zhou et al. [27] and many others.

RELAXED PROXIMAL POINT ALGORITHMS BASED ON A-AXIMAL RELAXED MONOTONICITY FRAMEWORKS WITH APPLICATIONS

  • Agarwal, Ravi P.;Verma, Ram U.
    • East Asian mathematical journal
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    • 제27권5호
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    • pp.545-555
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    • 2011
  • Based on the A-maximal(m)-relaxed monotonicity frameworks, the approximation solvability of a general class of variational inclusion problems using the relaxed proximal point algorithm is explored, while generalizing most of the investigations, especially of Xu (2002) on strong convergence of modified version of the relaxed proximal point algorithm, Eckstein and Bertsekas (1992) on weak convergence using the relaxed proximal point algorithm to the context of the Douglas-Rachford splitting method, and Rockafellar (1976) on weak as well as strong convergence results on proximal point algorithms in real Hilbert space settings. Furthermore, the main result has been applied to the context of the H-maximal monotonicity frameworks for solving a general class of variational inclusion problems. It seems the obtained results can be used to generalize the Yosida approximation that, in turn, can be applied to first- order evolution inclusions, and can also be applied to Douglas-Rachford splitting methods for finding the zero of the sum of two A-maximal (m)-relaxed monotone mappings.

Weak and Strong Convergence of Hybrid Subgradient Method for Pseudomonotone Equilibrium Problems and Nonspreading-Type Mappings in Hilbert Spaces

  • Sriprad, Wanna;Srisawat, Somnuk
    • Kyungpook Mathematical Journal
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    • 제59권1호
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    • pp.83-99
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    • 2019
  • In this paper, we introduce a hybrid subgradient method for finding an element common to both the solution set of a class of pseudomonotone equilibrium problems, and the set of fixed points of a finite family of ${\kappa}$-strictly presudononspreading mappings in a real Hilbert space. We establish some weak and strong convergence theorems of the sequences generated by our iterative method under some suitable conditions. These convergence theorems are investigated without the Lipschitz condition for bifunctions. Our results complement many known recent results in the literature.

Testing Gravitational Weak-lensing Maps with Galaxy Redshift Surveys: preliminary results

  • Ko, Jongwan;Utsumi, Yousuke;Hwang, Ho Seong;Dell'Antonio, Ian P.;Geller, Margaret J.;Yang, Soung-Chul;Kyeong, Jaemann
    • 천문학회보
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    • 제39권2호
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    • pp.45.2-45.2
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    • 2014
  • To measure the mass distribution of galaxy systems weak-lensing analysis has been widely used because it directly measures the total mass of a system regardless of its baryon content and dynamical state. However, the weak-lensing only provides a map of projected surface mass density. On the other hand, galaxy redshift surveys provide a map of the three-dimensional galaxy distribution. It thus can resolve the structures along the line of sight projected in the weak-lensing map. Therefore, the comparison of structures identified in the weak-lensing maps and in the redshift surveys is an important test of the issues limiting applications of weak-lensing to the identification of galaxy clusters. Geller et al. (2010) and Kurtz et al. (2012) compared massive clusters identified in a dense redshift survey with significant weak-lensing map convergence peaks. Both assessments of the efficiency of weak-lensing map for cluster identification did not draw a general conclusion, because the sample is so small. Thus, we additionally perform deep imaging observations of fields in a dense galaxy redshift survey that contain galaxy clusters at z~0.2-0.5, using CFHT Megacam.

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A CONVERGENCE THEOREM ON QUASI-ϕ-NONEXPANSIVE MAPPINGS

  • Kang, Shin Min;Cho, Sun Young;Kwun, Young Chel;Qin, Xiaolong
    • 충청수학회지
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    • 제23권1호
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    • pp.73-82
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    • 2010
  • In an infinite-dimensional Hilbert space, the normal Mann iteration has only weak convergence, in general, even for nonexpansive mappings. The purpose of this paper is to modify the normal Mann iteration to have strong convergence for a closed quasi-$\phi$-nonexpansive mapping in the framework of Banach spaces.