• Title/Summary/Keyword: Asymptotic limit

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SOME SHADOWING PROPERTIES OF THE SHIFTS ON THE INVERSE LIMIT SPACES

  • Tsegmid, Nyamdavaa
    • Journal of the Chungcheong Mathematical Society
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    • v.31 no.4
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    • pp.461-466
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    • 2018
  • $Let\;f:X{\rightarrow}X$ be a continuous surjection of a compact metric space X and let ${\sigma}_f:X_f{\rightarrow}X_f$ be the shift map on the inverse limit space $X_f$ constructed by f. We show that if a continuous surjective map f has some shadowing properties: the asymptotic average shadowing property, the average shadowing property, the two side limit shadowing property, then ${\sigma}_f$ also has the same properties.

Asymptotic Characteristics of MSE-Optimal Scalar Quantizers for Generalized Gamma Sources

  • Rhee, Ja-Gan;Na, Sang-Sin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.5A
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    • pp.279-289
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    • 2012
  • Characteristics, such as the support limit and distortions, of minimum mean-squared error (MSE) N-level uniform and nonuniform scalar quantizers are studied for the family of the generalized gamma density functions as N increases. For the study, MSE-optimal scalar quantizers are designed at integer rates from 1 to 16 bits/sample, and their characteristics are compared with corresponding asymptotic formulas. The results show that the support limit formulas are generally accurate. They also show that the distortion of nonuniform quantizers is observed to converge to the Panter-Dite asymptotic constant, whereas the distortion of uniform quantizers exhibits slow or even stagnant convergence to its corresponding Hui-Neuhoff asymptotic constant at the studied rate range, though it may stay at a close proximity to the asymptotic constant for the Rayleigh and Laplacian pdfs. Additional terms in the asymptote result in quite considerable accuracy improvement, making the formulas useful especially when rate is 8 or greater.

Asymptotics in Load-Balanced Tandem Networks

  • Lee, Ji-Yeon
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.10a
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    • pp.155-162
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    • 2003
  • A tandem network in which all nodes have the same load is considered. We derive bounds on the probability that the total population of the tandem network exceeds a large value by using its relation to the stationary distribution. These bounds imply a stronger asymptotic limit than that in the large deviation theory.

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Asymptotic Theory for Multi-Dimensional Mode Estimator

  • Kim, Jean-Kyung
    • Journal of the Korean Statistical Society
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    • v.23 no.2
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    • pp.251-269
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    • 1994
  • In this paper we extend Kim and Pollard's cube root asymptotics to other rates of convergence, to establish an asymptotic theory for a multidimensional mode estimator based on uniform kernel with shrinking bandwidths. We obtain rates of convergence depending on shrinking rates of bandwidth and non-normal limit distributions. Optimal decreasing rates of bandwidth are discussed.

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Asymptotics in Load-Balanced Tandem Networks

  • Lee, Ji-Yeon
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.3
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    • pp.715-723
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    • 2003
  • A tandem network in which all nodes have the same load is considered. We derive bounds on the probability that the total population of the tandem network exceeds a large value by using its relation to the stationary distribution. These bounds imply a stronger asymptotic limit than that in the large deviation theory.

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The Asymptotic Properties of Mean Residual Life Function on Left Truncated and Right Censoring Model

  • Moon, Kyoung-Ae;Shin, Im-Hee
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.1
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    • pp.99-109
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    • 1997
  • The estimation procedure of mean residual life function has been placed an important role in the study of survival analysis. In this paper, the product limit estimator on left truncated and right censoring model is proposed with asymptotic properties. Also, the small sample properties are investigated through the Monte Carlo study and the proposed product limit type estimator is compared with ordinary Kaplan-Meier type estimator.

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VARIOUS SHADOWING PROPERTIES FOR INVERSE LIMIT SYSTEMS

  • Lee, Manseob
    • Journal of the Chungcheong Mathematical Society
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    • v.29 no.4
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    • pp.657-661
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    • 2016
  • Let $f:X{\rightarrow}X$ be a continuous surjection of a compact metric space and let ($X_f,{\tilde{f}}$) be the inverse limit of a continuous surjection f on X. We show that for a continuous surjective map f, if f has the asymptotic average, the average shadowing, the ergodic shadowing property then ${\tilde{f}}$ is topologically transitive.

ASYMPTOTIC LIMITS FOR THE SELF-DUAL CHERN-SIMONS CP(1) MODEL

  • HAN, JONG-MIN;NAM, HEE-SEOK
    • Communications of the Korean Mathematical Society
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    • v.20 no.3
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    • pp.579-588
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    • 2005
  • In this paper we study the asymptotics for the energy density in the self-dual Chern-Simons CP(1) model. When the sequence of corresponding multivortex solutions converges to the topological limit, we show that the field configurations saturating the energy bound converges to the limit function. Also, we show that the energy density tends to be concentrated at the vortices and antivortices as the Chern-Simons coupling constant $\kappa$ goes to zero.

Asymptotic Density of Quadratic Forms

  • 최기현
    • The Korean Journal of Applied Statistics
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    • v.4 no.2
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    • pp.149-156
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    • 1991
  • The theory of the asymptotic behavior of Toeplitz forms is applicable to some problems concerning the local limit theorem.

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ASYMPTOTIC DEPENDENCE BETWEEN RANDOM CENTRAL QUASI-RANGES AND RANDOM EMPIRICAL QUANTILES

  • Nigm, E.M.
    • Journal of applied mathematics & informatics
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    • v.16 no.1_2
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    • pp.289-302
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    • 2004
  • The asymptotic dependence between the central quasi-ranges and empirical quantiles was studied. The asymptotic dependence are obtained when the sample size is a positive integer valued random variable (r. v.). The dependence conditions and limit forms are obtained under generl conditions such as : the interrelation of the basic variables (the original random sample) and the random sample size is not restricted. In additition the normalizing constants do not depend on the random size.