• 대한수학회논문집
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• 제37권3호
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• pp.765-800
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• 2022

Quantization for probability distributions concerns the best approximation of a d-dimensional probability distribution P by a discrete probability with a given number n of supporting points. In this paper, we have considered a probability measure generated by an infinite iterated function system associated with a probability vector on ℝ. For such a probability measure P, an induction formula to determine the optimal sets of n-means and the nth quantization error for every natural number n is given. In addition, using the induction formula we give some results and observations about the optimal sets of n-means for all n ≥ 2.

• Korean Journal of Mathematics
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• 제28권2호
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• pp.323-341
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• 2020

In this note, we investigate the multifractal analogues of the Hewitt-Stromberg measures and dimensions in a probability space.

• 한국군사과학기술학회지
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• 제16권2호
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• pp.118-129
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• 2013

Since the obstacles and mines are of the risk factors for operating ships and submarines, the active sonar system is inevitably used to avoid the hazards in ocean environment. In this paper, modeling and simulation algorithm is used for active sonar systemto quantify the measure of mission achievability, which is known as Measure of Effectiveness(MOE), specifically for detection in this study. MOE for detection is directly formulated as a Cumulative Detection Probability(CDP) calculated from Probability of Detection(PD) in range and azimuth. The detection probability is calculated from Transmission Loss(TL) and the sonar parameters such asDirectivity Index (DI) calculated from the shape of transmitted and received array, steered beam patterns, and Reverberation Level (RL). The developed code is applied to demonstrating its applicability.

• 해양환경안전학회지
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• 제2권1호
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• pp.97-106
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• 1996

One of the main problems in evaluating complex objects, such as an ill-defined system, is how to treat ambiguous aspect of the evaluation. Due to the Complexity and ambiguity of the objects, many types of evaluation attributes should be identified based on the rational dsision. One of these attributes is an analytical hierarchy process (AHP). the weight of evaluation attribtes in AHP however comes from the probability measure based on the additivity. Therefore, it is notapplicable to the objects which have the property of non-additivity. In the previous studies by other researchers they intriduced the Hierarchical Fuzzy Integral method or mergd AHP and fuzzy measure for the analysis of the overlaps among the evaluation objects. But, they need more anlyses in terms of transformation of the probability measure into fuzzy measure which fits for the additivity and overlapping coefficient which affects to the fuzzy measure. Considering these matters, this paper deals that, ⅰ) clarifying the relation between the fuzzy and probability measure adopted in AHP, ii) calculating directly the family of fuzzy measure from the overlapping coefficient and probability measure. A simple algorithm for the calculation of fuzzy measures and set family of those from the above results is also proposed. Finally, the effectiveness of the algorithm developed by applying this to the problems for estimation of safety in ship berthing and for evaluation of ports in competition is verified. This implied that the new algoritnm gives better description of the system evaluation.

• 한국군사과학기술학회지
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• 제15권5호
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• pp.601-614
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• 2012

Since the optimized use of sonar systems available for detection is a very practical problem for a given ocean environment, the measure of mission achievability is needed for operating the sonar system efficiently. In this paper, a theory on Measure Of Effectiveness(MOE) for specific mission such as detection is described as the measure of mission achievability, and a recursive Cumulative Detection Probability(CDP) algorithm is found to be most efficient from comparing three CDP algorithms for discrete glimpses search to reduce computation time and memory for complicated scenarios. The three CDPs which are MOE for sonar-maneuver pattern are calculated as time evolves for comparison, based on three different formula depending on the assumptions as follows; dependent or independent glimpses, unimodal or non-unimodal distribution of Probability of Detection(PD) as a function of observation time interval for detection. The proposed CDP algorithm which is made from unimodal formula is verified and applied to OASPP(Optimal Acoustic Search Path Planning) with complicated scenarios.

• 한국군사과학기술학회지
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• 제15권3호
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• pp.272-287
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• 2012

The optimal use of sonar systems for detection is a practical problem in a given ocean environment. In order to quantify the mission achievability in general, measure of effectiveness(MOE) is defined for specific missions. In this paper, using the specific MOE for detection, which is represented as cumulative detection probability(CDP), an integrated software package named as Optimal Acoustic Search Path Planning(OASPP) is developed. For a given ocean environment and sonar systems, the discrete observations for detection probability(PD) are used to calculate CDP incorporating sonar and environmental parameters. Also, counter-detection probability is considered for vulnerability analysis for a given scenario. Through modeling and simulation for a simple case for which an intuitive solution is known, the developed code is verified.

• 대한수학회논문집
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• 제37권4호
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• pp.1073-1097
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• 2022

In this paper, we shall be concerned with evaluation of multifractal Hausdorff measure 𝓗^q,t_𝜇 and multifractal packing measure 𝓟^q,t_𝜇 of Cartesian product sets by means of the measure of their components. This is done by investigating the density result introduced in [34]. As a consequence, we get the inequalities related to the multifractal dimension functions, proved in [35], by using a unified method for all the inequalities. Finally, we discuss the extension of our approach to studying the multifractal Hewitt-Stromberg measures of Cartesian product sets.

• 한국경영과학회지
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• 제31권1호
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• pp.15-24
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• 2006

In simulation input modeling, it is important to identify a probability distribution to represent the input process of interest. In this paper, an appropriate sample size is determined for parameter estimation associated with some typical probability distributions frequently encountered in simulation input modeling. For this purpose, a statistical measure is proposed to evaluate the effect of sample size on the precision as well as the accuracy related to the parameter estimation, square rooted mean square error to parameter ratio. Based on this evaluation measure, this sample size effect can be not only analyzed dimensionlessly against parameter's unit but also scaled regardless of parameter's magnitude. In the Monte Carlo simulation experiments, three continuous and one discrete probability distributions are investigated such as ; 1) exponential ; 2) gamma ; 3) normal ; and 4) poisson. The parameter's magnitudes tested are designed in order to represent distinct skewness respectively. Results show that ; 1) the evaluation measure drastically improves until the sample size approaches around 200 ; 2) up to the sample size about 400, the improvement continues but becomes ineffective ; and 3) plots of the evaluation measure have a similar plateau pattern beyond the sample size of 400. A case study with real datasets presents for verifying the experimental results.

• Journal of the Korean Statistical Society
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• 제18권1호
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• pp.62-71
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• 1989

We consider a Markov proces ${X_n} on [0,\infty)^k$ which is generated by $X_{n+1} = f(X_n) + \varepsilon_{n+1}$ where f is a continuous, nondecreasing concave function. Sufficient conditions for the existence of a unique invariant probability measure for ${X_n}$ are obtained.

• 대한수학회지
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• 제36권4호
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• pp.699-705
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• 1999

Given a probability space and a subsigma algebra A, each measure equivalent to the probability measure generates a different conditional expectation operator. We characterize those which act boundedly on the original $L^2$ space, and show there are sufficiently many such conditional expectations to generate the commutant of $L^{\infty}$ (A).