• Title/Summary/Keyword: Random Process

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Stochastic response of colored noise parametric system

  • Heo, Hoon;Paik, Jong-Han;Oh, Jin-Hyoung
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.451-455
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    • 1993
  • Interaction between system and disturbance results in system with time-dependent parameter. Parameter variation due to interaction has random characteristics. Most of the randomly varying parameters in control problem is regarded as white noise random process which is not a realistic model. In real situation those random variation is colored noise random process. Modified F-P-K equation is proposed to get the response of the random parametric system using some correction factor. Proposed technique is employed to obtain the colored noise parametric system response and confirmed via Monte-Carlo Simulation.

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A STRONG LAW OF LARGE NUMBERS FOR AANA RANDOM VARIABLES IN A HILBERT SPACE AND ITS APPLICATION

  • Ko, Mi-Hwa
    • Honam Mathematical Journal
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    • v.32 no.1
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    • pp.91-99
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    • 2010
  • In this paper we introduce the concept of asymptotically almost negatively associated random variables in a Hilbert space and obtain the strong law of large numbers for a strictly stationary asymptotically almost negatively associated sequence of H-valued random variables with zero means and finite second moments. As an application we prove a strong law of large numbers for a linear process generated by asymptotically almost negatively random variables in a Hilbert space with this result.

Optimal Inspection Period for the System Subject to Random Shocks

  • Kim, Sung-Soon;Choi, Seung-Kyoung;Lee, Eui-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.725-733
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    • 2005
  • A system subject to random shocks is considered. The shocks arrive according to a Poisson process and the amount of each shock is exponentially distributed. In this paper, a periodic inspection policy for the system is compared with a random inspection policy. After assigning several maintenance costs to the system, we calculate and compare the long-run average costs per unit time under two policies.

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A Random Shock Model for a Linearly Deteriorating System

  • Lee, Ji-Yeon;Lee, Eui-Young
    • Journal of the Korean Statistical Society
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    • v.24 no.2
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    • pp.471-479
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    • 1995
  • A random shock model for a linearly deteriorating system is introduced. The system deteriorating linearly with time is subject to random shocks which arrive according to a Poisson process and decrease the state of the system by a random amount. The system is repaired by a repairmen arriving according to another Poisson process if the state when he arrives is below a threshold. Explicit expressions are deduced for the characteristic function of the distribution function of X(t), the state of the system at time t, and for the distribution function of X(t) if X(t) is over the threshold. The stationary case is briefly discussed.

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RENEWAL AND RENEWAL REWARD THEORIES FOR T-INDEPENDENT FUZZY RANDOM VARIABLES

  • KIM, JAE DUCK;HONG, DUG HUN
    • Journal of applied mathematics & informatics
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    • v.33 no.5_6
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    • pp.607-625
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    • 2015
  • Recently, Wang et al. [Computers and Mathematics with Ap-plications 57 (2009) 1232-1248.] and Wang and Watada [Information Sci-ences 179 (2009) 4057-4069.] studied the renewal process and renewal reward process with fuzzy random inter-arrival times and rewards under the T-independence associated with any continuous Archimedean t-norm. But, their main results do not cover the classical theory of the random elementary renewal theorem and random renewal reward theorem when fuzzy random variables degenerate to random variables, and some given assumptions relate to the membership function of the fuzzy variable and the Archimedean t-norm of the results are restrictive. This paper improves the results of Wang and Watada and Wang et al. from a mathematical per-spective. We release some assumptions of the results of Wang and Watada and Wang et al. and completely generalize the classical stochastic renewal theorem and renewal rewards theorem.

Cost-Efficient and Automatic Large Volume Data Acquisition Method for On-Chip Random Process Variation Measurement

  • Lee, Sooeun;Han, Seungho;Lee, Ikho;Sim, Jae-Yoon;Park, Hong-June;Kim, Byungsub
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.15 no.2
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    • pp.184-193
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    • 2015
  • This paper proposes a cost-efficient and automatic method for large data acquisition from a test chip without expensive equipment to characterize random process variation in an integrated circuit. Our method requires only a test chip, a personal computer, a cheap digital-to-analog converter, a controller and multimeters, and thus large volume measurement can be performed on an office desk at low cost. To demonstrate the proposed method, we designed a test chip with a current model logic driver and an array of 128 current mirrors that mimic the random process variation of the driver's tail current mirror. Using our method, we characterized the random process variation of the driver's voltage due to the random process variation on the driver's tail current mirror from large volume measurement data. The statistical characteristics of the driver's output voltage calculated from the measured data are compared with Monte Carlo simulation. The difference between the measured and the simulated averages and standard deviations are less than 20% showing that we can easily characterize the random process variation at low cost by using our cost-efficient automatic large data acquisition method.

ON THE LARGE AND SMALL INCREMENTS OF GAUSSIAN RANDOM FIELDS

  • Zhengyan Lin;Park, Yong-Kab
    • Journal of the Korean Mathematical Society
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    • v.38 no.3
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    • pp.577-594
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    • 2001
  • In this paper we establish limit theorems on the large and small increments of a two-parameter Gaussian random process on rectangles in the Euclidean plane via estimating upper bounds of large deviation probabilities on suprema of the two-parameter Gaussian random process.

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A Note on the Strong Mixing Property for a Random Coefficient Autoregressive Process

  • Lee, Sang-Yeol
    • Journal of the Korean Statistical Society
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    • v.24 no.1
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    • pp.243-248
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    • 1995
  • In this article we show that a class of random coefficient autoregressive processes including the NEAR (New exponential autoregressive) process has the strong mixing property in the sense of Rosenblatt with mixing order decaying to zero. The result can be used to construct model free prediction interval for the future observation in the NEAR processes.

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A Central Limit Theorem for the Linear Process in a Hilbert Space under Negative Association

  • Ko, Mi-Hwa
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.687-696
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    • 2009
  • We prove a central limit theorem for the negatively associated random variables in a Hilbert space and extend this result to the linear process generated by negatively associated random variables in a Hilbert space. Our result implies an extension of the central limit theorem for the linear process in a real space under negative association to a simplest case of infinite dimensional Hilbert space.