• Title/Summary/Keyword: random vectors

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A Weighted Random Pattern Testing Technique for Path Delay Fault Detection in Combinational Logic Circuits (조합 논리 회로의 경로 지연 고장 검출을 위한 가중화 임의 패턴 테스트 기법)

  • 허용민;임인칠
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.32A no.12
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    • pp.229-240
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    • 1995
  • This paper proposes a new weighted random pattern testing technique to detect path delay faults in combinational logic circuits. When computing the probability of signal transition at primitive logic elements of CUT(Circuit Under Test) by the primary input, the proposed technique uses the information on the structure of CUT for initialization vectors and vectors generated by pseudo random pattern generator for test vectors. We can sensitize many paths by allocating a weight value on signal lines considering the difference of the levels of logic elements. We show that the proposed technique outperforms existing testing method in terms of test length and fault coverage using ISCAS '85 benchmark circuits. We also show that the proposed testing technique generates more robust test vectors for the longest and near-longest paths.

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A NOTE ON SUMS OF RANDOM VECTORS WITH VALUES IN A BANACH SPACE

  • Hong, Dug-Hun;Kwon, Joong-Sung
    • Communications of the Korean Mathematical Society
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    • v.10 no.2
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    • pp.439-442
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    • 1995
  • Let ${X_n : n = 1,2,\cdots}$ be a sequence of pairwise independent identically distributed random vectors taking values in a separable Hilbert space H such that $E \Vert X_1 \Vert = \infty$. Let $S_n = X_1 + X_2 + \cdots + X_n$ and for any real $\alpha$ with $0 < \alpha < 1$ define a sequence ${\gamma_n(\alpha)}$ as $\gamma_n(\alpha) = inf {r : P(\Vert S_n \Vert \leq r) \geq \alpha}$. Then $$ lim_{n \to \infty} sup \Vert S_n \Vert/\gamma_n(\alpha) = \infty $$ holds. This is a generalization of Vvedenskaya[2].

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THE CENTRAL LIMIT THEOREMS FOR THE MULTIVARIATE LINEAR PROCESSES GENERATED BY NEGATIVELY ASSOCIATED RANDOM VECTORS

  • Kim, Tae-Sung;Ko, Mi-Hwa;Ro, Hyeong-Hee
    • The Pure and Applied Mathematics
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    • v.11 no.2
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    • pp.139-147
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    • 2004
  • Let {<$\mathds{X}_t$} be an m-dimensional linear process of the form $\mathbb{X}_t\;=\sumA,\mathbb{Z}_{t-j}$ where {$\mathbb{Z}_t$} is a sequence of stationary m-dimensional negatively associated random vectors with $\mathbb{EZ}_t$ = $\mathbb{O}$ and $\mathbb{E}\parallel\mathbb{Z}_t\parallel^2$ < $\infty$. In this paper we prove the central limit theorems for multivariate linear processes generated by negatively associated random vectors.

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A PARTIAL ORDERING OF WEAK POSITIVE QUADRANT DEPENDENCE

  • Kim, Tae-Sung;Lee, Young-Ro
    • Communications of the Korean Mathematical Society
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    • v.11 no.4
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    • pp.1105-1116
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    • 1996
  • A partial ordering is developed among weakly positive quadrant dependent (WPQD) bivariate random vectors. This permits us to measure the degree of WPQD-ness and to compare pairs of WPQD random vectors. Some properties and closures under certain statistical operations are derived. An application is made to measures of dependence such as Kendall's $\tau$ and Spearman's $\rho$.

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A PARTIAL ORDERING OF CONDITIONALLY POSITIVE QUADRANT DEPENDENCE

  • Baek, Jong-Il;Choi, Jeong-Yeol;Park, Chun-Ho
    • Communications of the Korean Mathematical Society
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    • v.16 no.2
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    • pp.297-308
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    • 2001
  • A partial ordering is developed here among conditionally positive quadrant dependent (CPQD) bivariate random vectors. This permits us to measure the degree of CPQD-ness and to compare pairs of CPQD random vectors. Some properties and closure under certain statistical operations are derived.

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Relative Frequency of Order Statistics in Independent and Identically Distributed Random Vectors

  • Park, So-Ryoung;Kwon, Hyoung-Moon;Kim, Sun-Yong;Song, Iick-Ho
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.243-254
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    • 2006
  • The relative frequency of order statistics is investigated for independent and identically distributed (i.i.d.) random variables. Specifically, it is shown that the probability $Pr\{X_{[s]}=x\}$ is no less than the probability $Pr\{X_{[r]}=x\}$ at any point $x{\geqq}x_0$ when r$X_{[r]}$ denotes the r-th order statistic of an i.i.d. discrete random vector and $x_0$ depends on the population probability distribution. A similar result for i.i.d. continuous random vectors is also presented.

ON SIDON SETS IN A RANDOM SET OF VECTORS

  • Lee, Sang June
    • Journal of the Korean Mathematical Society
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    • v.53 no.3
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    • pp.503-517
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    • 2016
  • For positive integers d and n, let $[n]^d$ be the set of all vectors ($a_1,a_2,{\cdots},a_d$), where ai is an integer with $0{\leq}a_i{\leq}n-1$. A subset S of $[n]^d$ is called a Sidon set if all sums of two (not necessarily distinct) vectors in S are distinct. In this paper, we estimate two numbers related to the maximum size of Sidon sets in $[n]^d$. First, let $\mathcal{Z}_{n,d}$ be the number of all Sidon sets in $[n]^d$. We show that ${\log}(\mathcal{Z}_{n,d})={\Theta}(n^{d/2})$, where the constants of ${\Theta}$ depend only on d. Next, we estimate the maximum size of Sidon sets contained in a random set $[n]^d_p$, where $[n]^d_p$ denotes a random set obtained from $[n]^d$ by choosing each element independently with probability p.

PACKING DIMENSIONS OF GENERALIZED RANDOM MORAN SETS

  • Tong, Xin;Yu, Yue-Li;Zhao, Xiao-Jun
    • Journal of the Korean Mathematical Society
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    • v.51 no.5
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    • pp.1075-1088
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    • 2014
  • We consider random fractal sets with random recursive constructions in which the contracting vectors have different distributions at different stages. We prove that the random fractal associated with such construction has a constant packing dimension almost surely and give an explicit formula to determine it.

On a functional central limit theorem for the multivariate linear process generated by positively dependent random vectors

  • KIM TAE-SUNG;BAEK JONG IL
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.119-121
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    • 2000
  • A functional central limit theorem is obtained for a stationary multivariate linear process of the form $X_t=\sum\limits_{u=0}^\infty{A}_{u}Z_{t-u}$, where {$Z_t$} is a sequence of strictly stationary m-dimensional linearly positive quadrant dependent random vectors with $E Z_t = 0$ and $E{\parallel}Z_t{\parallel}^2 <{\infty}$ and {$A_u$} is a sequence of coefficient matrices with $\sum\limits_{u=0}^\infty{\parallel}A_u{\parallel}<{\infty}$ and $\sum\limits_{u=0}^\infty{A}_u{\neq}0_{m{\times}m}$. AMS 2000 subject classifications : 60F17, 60G10.

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