• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.371-382
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• 2005

The paper compares the performance of some widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained Bayes estimator by means of a new measurement under squared error loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.283-293
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• 2010

In this paper, inverse constrained minimum spanning tree problem under Hamming distance. Such an inverse problem is to modify the weights with bound constrains so that a given feasible solution becomes an optimal solution, and the deviation of the weights, measured by the weighted Hamming distance, is minimum. We present a strongly polynomial time algorithm to solve the inverse constrained minimum spanning tree problem under Hamming distance.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1017-1028
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• 2014

Well-known Bayes and empirical Bayes estimators have a disadvantage in respecting to overshink the parameter estimator error; therefore, a constrained Bayes estimator is suggested by matching the first two moments. Also traditional loss function such as mean square error loss function only considers the precision of estimation and to consider both precision and goodness of fit, balanced loss function is suggested. With these reasons, constrained Bayes estimators under balanced loss function is recommended for non-life insurance pricing.; however, most studies focus on the performance of estimation since Bayes risk of newly suggested estimators such as constrained Bayes and constrained empirical Bayes estimators under specific loss function is difficult to derive. This study compares the Bayes risk of several Bayes estimators under two different loss functions for estimating the risk in the auto insurance business and indicates the effectiveness of the newly suggested Bayes estimators with regards to Bayes risk perspective through auto insurance real data analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2121-2125
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• 2003

This paper proposes a fast distributed constrained power control (FDCPC) with non-stationary relaxation factor to next power update in CDMA cellular power control system. We review unconstrained control algorithms, the distributed power control (DPC), unconstrained second order power control (USOPC) and DPC with stationary relaxation factor (DPCSRF). Under the unconstrained condition, the convergence analysis shows theoretically that the convergence rate of DPC is the fastest one. However, under the constrained control algorithms, DCPC is not the fastest one any more because of transmission power constraint. To improve the convergence speed, the DCPC with non-stationary relaxation factor (FDCPC) are proposed. Under the constrained condition, the convergence rate of FDCPC outperforms that of DCPC and CSOPC.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.235-243
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• 2014

Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and empirical Bayes estimates produce by matching first and second empirical moments; subsequently, a constrained Bayes estimate is recommended to use in case the research objective is to produce a histogram of the estimates considering the location and dispersion. The well-known squared error loss function exclusively emphasizes the precision of estimation and may lead to biased estimators. Thus, the balanced loss function is suggested to reflect both goodness of fit and precision of estimation. In insurance pricing, the accurate location estimates of risk and also dispersion estimates of each risk group should be considered under proper loss function. In this paper, by applying these two ideas, the benefit of the constrained Bayes estimates and balanced loss function will be discussed; in addition, application effectiveness will be proved through an analysis of real insurance accident data.

• ETRI Journal
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• v.24 no.3
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• pp.239-246
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• 2002

We investigate an alternative blind adaptive multiuser detection scheme based on a non-canonical linearly constrained constant modulus (LCCM) criterion and prove that, under the constrained condition, the non-canonical linearly constrained constant modulus algorithm (LCCMA) can completely remove multiple -access interference. We further demonstrate that the non-canonical LCCM criterion function is strictly convex in the noise-free state, and that under the constrained condition, it is also strictly convex even where small noise is present. We present a simple method for selecting the constant as well as a stochastic gradient algorithm for implementing our scheme. Numerical simulation results verify the scheme's efficiency.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.759-772
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• 2012

In this paper, semi-infinite constrained programming, a class of constrained nonsmooth optimization problems, are transformed into unconstrained nonsmooth convex programs under the help of exact penalty function. The unconstrained objective function which owns the primal-dual gradient structure has connection with $\mathcal{VU}$-space decomposition. Then a $\mathcal{VU}$-space decomposition method can be applied for solving this unconstrained programs. Finally, the superlinear convergence algorithm is proved under certain assumption.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.7
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• pp.261-266
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• 2001

The flexural vibration of laminated composite beams with active and passive constrained layer damping has been investigated to design a structure with maximum possible damping capacity. The equations of motion are derived fro flexural vibrations of symmetrical,. multi-layer laminated beams. The damping ratio and model damping of the first bending mode are calculated by means of iterative complex eigensolution method. The direct negative velocity feedback control is used for the active constrained layer damping. It is shown that the flexible laminated beam is more effective in the vibration control for both active and passive constrained layer damping. and this paper addresses a design strategy of laminated composite under flexural vibrations with constrained layer damping.

• Journal of the Korean Society of Safety
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• v.22 no.5
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• pp.13-20
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• 2007

Elastomeric O-ring seals are widely used in static and dynamic applications. A compressed and highly pressurized O-ring seal inserted under laterally one-sided constrained condition has been analyzed experimentally and numerically. The deformed shape and extrusion length of the O-ring under high pressure has been measured by the computed tomography. Through the comparison of experimental and FE results, the numerical analysis technique has been verified. Using verified FE method, the contact stress profiles at sealing surfaces have been investigated and their relevance to the 0-ring performance evaluated based on stress-related and displacement-related parameters. It has been found that the contact stress profiles and deformation behaviors of the seal are affected by friction coefficient, gap clearance, and pressure considerably.