• 대한산업공학회지
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• 제36권4호
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• pp.212-218
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• 2010

This paper shows accuracy comparison results of reliability estimation methods for one-shot systems with respect to sample sizes. To compare accuracy in reliability estimation methods, quantal-response data, characterizing one-shot systems, were simulated using failure times of LED obtained through the accelerated life test, and then the true reliability over time was evaluated using the failure times. The simulated quantal-response data were used to estimate the true reliability through applying reliability estimation methods in open literature. Accuracy of each reliability estimation method was compared in terms of both SSE (Sum of Squared Error) and MSE (Mean Squared Error), and then estimation trend for each method is found. Feasible bounds which true reliability would exist within were estimated through applying the found trends to quantal-response data set of a real weapon system.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제4권1호
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• pp.49-65
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• 2000

A method for inverting the Laplace transform is presented, using a finite series of the classical Legendre polynomials. The method recovers a real-valued function f(t) in a finite interval of the positive real axis when f(t) belongs to a certain class ${\mathcal{W}}_{\beta}$ and requires the knowledge of its Laplace transform F(s) only at a finite number of discrete points on the real axis s > 0. The choice of these points will be carefully considered so as to improve the approximation error as well as to minimize the number of steps needed in the evaluations. The method is tested on few examples, with particular emphasis on the estimation of the error bounds involved.

• 대한수학회지
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• 제34권2호
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• pp.293-307
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• 1997

In this paper we present the $L^2$-estimation for the kernel $K_n$ of the remaider term for the Gaussian quadrature with respect to one of four Chebyshev weight functions and the error bound of the type on the contour $$ $\mid$R_n(f)$\mid$ \leq \frac{2\pi}{\sqrt{l(\Gamma)}} max_{z\in\Gamma}$\mid$f(z)$\mid$ (\smallint_\Gamma $\mid$K_n(z)$\mid$^2$\mid$dz$\mid$)^\frac{2}{1}, $$ where $l(\Gamma)$ denotes the length of the contour $\Gamma$.

• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.256-262
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• 2000

This paper proposes a new sliding mode controller combined with a multi-layer neural network using the error back propagation learning algorithm,, The network acts as a compensator of the conventional sliding mode controller to improve the control performance when initial assumptions of uncertainty bounds of system parameters are violated. The proposed controller can reduce th steady state error of conventional sliding mode controller with the boundary layer technique Computer simulation results show that the proposed method is effective to control dynamic systems with unexpectably large uncertainties.

• 산업경영시스템학회지
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• 제27권2호
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• pp.24-28
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• 2004

This paper considers a scheduling problem concerned with an assembly system where two components are first treated In their own parallel machines and then pulled to be assembled into a final product at a single assembly machine. The objective measure is the mean completion time of jobs(a finite number of products). Through characterizing solution properties, we obtain the worst case error bounds of an arbitrary permutation and a SPT based heuristic.

• Fibers and Polymers
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• 제6권4호
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• pp.348-354
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• 2005

These days consumers' various demands are accelerating research on apparel manufacturing system including automatic measurement, pattern generation, and clothing simulation. Accordingly, methods of reconstructing human body from point-clouds measured using a three dimensional scanning device are required for apparel CAD system to support these functions. In particular, we present in this study a human body reconstruction method focused on two issues, which are the decision of the number of control point for each sectional curve with error bound and the local knot removal for reducing the unusual concentration of control points. The approximation of sectional curves with error bounds as an approximation criterion leads all sectional curves to their own particular shapes apart from the number of control points. In addition, the application of the local knot removal to construction of human body sectional curves reduces the unusual concentration of control points effectively. The results may be used to produce an apparel CAD system as an automatic pattern generation system and a clothing simulation system through the low level control of NUBS or NURBS.

• 응용통계연구
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• 제16권1호
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• pp.169-179
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• 2003

동일조사에서 통계분석 자가 흔히 범하는 오류 두 가지를 제시하였다. 하나는 일반적인 조사에서 발표된 조사결과로부터 두 비율의 비교를 시도할 때 범하기 쉬운 오류이고, 다른 하나는 중립적 응답 항목이 있을 때 통계전문가가 아닌 사람들 가운데에서 범하기 쉬운 잘못이다. 이런 오류들을 제시하고, 통계적으로 정확한 방법과 비교하여 잘못 사용하는 방법들이 갖는 문제들을 보여 줌으로써 교육 자료로 활용할 수 있도록 했다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.681-684
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• 2000

Gradient-type algorithms for adaptive IIR notch filters are very attractive in terms of both performances and computational requirements. Generally, it is quite difficult to assess their performances analytically. There have been several trials to analyze such adaptive algorithms as the sign and the plain gradient algorithms for some types of adaptive IIR notch filters, but many of them still remain unexplored. Furthermore, analysis techniques used in those trials can not be directly applied to different types of adaptive IIR notch filters. This paper presents a detailed performance analysis of the sign algorithm for a well-known adaptive IIR notch filter with constrained poles and zeros, which can not be done by just applying the related existing analysis techniques, and therefore has not been attempted yet. The steady-state estimation error and mean square error (MSE) of the algorithm are derived in closed forms. Stability bounds of the algorithm are also assessed. extensive simulations are conducted to support the analytical findings.

• International Journal of Reliability and Applications
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• 제13권2호
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• pp.71-80
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• 2012

This paper introduces a new approach for evaluating reliability of a complex system in terms of distributional parameters where analytical determination of reliability is intractable. The concept of discrete approximation, reported in the literature so far, fails to meet the latter requirement in terms of distributional parameters. The current work aims at offering a bound based approach where reliability planners not only get a clear idea about the extent of error but also can manipulate in terms of distributional parameters. This reliability approximation has been under taken under the Weibull frame work which is the most widely used model for reliability analysis. Numerical study has been carried out to examine the strength of our proposed reliability approximation via closeness between the two reliability bounds. This approach will be very useful during the early stages of product design as the distributional parameters can be adjusted.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.474-478
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• 1998

A new approach for the decision feedback equalizer(DFE) based on the back-propagation neural networks is described. We propose the method of optimal structure for back-propagation neural networks model. In order to construct an the optimal structure, we first prescribe the bounds of learning procedure, and the, we employ the method of incrementing the number of input neuron by utilizing the derivative of the error with respect to an hidden neuron weights. The structure is applied to the problem of adaptive equalization in the presence of inter symbol interference(ISI), additive white Gaussian noise. From the simulation results, it is observed that the performance of the propose neural networks based decision feedback equalizer outperforms the other two in terms of bit-error rate(BER) and attainable MSE level over a signal ratio and channel nonlinearities.