• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.50-57
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• 1997

영광 2호기 9주기 노심을 대상으로 다양한 운전조건에서 노외계측기 weighting function을 계산하고 영향 인자들에 대한 민감도 분석을 수행하였다. Weighting function 계산은 2차원 각분할 수송코드인 DORT 2.8.14를 사용하였고 핵단면적 라이브러리는 ENDF/B-VI에 근거한 BUGLE93 라이브러리를 사용하였다. Weighting function은 축방향 weighting function(R-Z 모델)과 집합체별 weighting function(R- 모델)을 계산하였고, 민감도 분석에 사용한 인자는 출력준위, 연소도, 제어봉 삽입, 붕소농도이다. 민감도 분석결과 노외계측기 weighting function은 출력 준위에 민감하고 그외 모든 인자의 영향은 무시할 수 있을 만큼 작았다. 또한 출력분포와 weighting function으로부터 계산되는 단순노외계측기 교정법의 계측기반응상수는 출력준위와 연소도를 고려하여 생산해야함을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.921-926
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• 2003

This paper describes a new type of the spatial filter detector (SFD) with variable and multi-valued weighting function. This SFD called variable spatial filter detector with multi-valued weighting function (VSFDwMWF) uses current-mode circuits for noise resistance and high-resolution weighting values. Total weighting values consist of 7bit, 6-signal bit and 1-sign bit. We fabricate VSFDwMWF chip using Rohm 0.35${\mu}$m CMOS process. VSFDwMWF chip includes two-dimensional 10${\times}$13 photodiode array and current-mode weighting control circuit. Simulation shows the weighting values are varied and multi-valued by external switching operation. The layout of VSFDwMWF chip is shown.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.481-483
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• 1998

In general, spatial filtering method was proposed to simplify measurement system through parallel Processing hardware. Spatial filtering is a method of detection that we can get a spatial pattern information, as we process a special space pattern, to say, as we process spatial parallel process by using the spatial weighting function. The important processing characteristics will be depended in according to how ire design a spatial weighting function, a spatial sensitive distribution. The form of the weighting function which is realized from the generally used spatial filtering is fixed and the weighting value was already became a binary-value. In this paper, we propose a new method in order to construct adaptive measurement systems. This method is a weighting function design to make multi-valued and variable.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.5-26
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• 2001

This paper proposes a new approach to identifying the unknown parameters of continuous LTI systems. For parameter identification in continuous-time systems, the Linear Integral Filter (LIF) method generally has been used in the beginning. Especially, one of the most efficient LIF methods in the literature is to use a weighting function satisfying specific three constraints. In high order systems, even though the weighting function satisfies the three constraints, it is impossible to identify the exact parameters of the systems because of information loss arising from a great amount of magnitude differences among the weighting function and its high-order derivatives. This paper, using an LMI technique, shows the limitation in designing the weighting function of the existing methods, and ...

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.137-143
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• 2010

This paper deals with the performance comparison of self adaptive equalizer by the weighting factor of MCMA cost function for the compensate the amplitude and phase distortion which occurs in the communication channel. The MCMA is improves the cost function of present CMA at the output of equalizer for the minimize of error function in the amplitude and phase, the value of weighting factor is used at this time. When the comparison of equalizer performance, we classified to initial state and steady state, then it represents the convergence time and convergence speed and steady state operation of equalizer to the predetermined level, it is determined by the weighting factor. We confirm to the different result to this 2 state by weighting factor values using computer simulation. By using the result of this paper, if we appropriately choose the weighting factor values in the environment of communication channel, it is expected that the high quality digital transmission is possible.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.6 s.99
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• pp.680-686
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• 2005

This paper introduces the robust design of an intake system using transmission loss and the frequency weighting function. First, transmission loss is measured to evaluate the performance of the noise reduction for the intake system. The robust design parameters of the intake system are extracted by adapting a cost function with the Taguchi method. Subsequently, the frequency weighting function is developed by the subjective evaluation in which 6 special engineers were participated. Finally, the comparison between the proposed frequency weighted optimal design and unweighted optimal design for the transmission loss as the part is performed. Here, the overall levels of the transmission loss according to the methods are presented to validate the effectiveness of the proposed methodology.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.547-552
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• 2007

In this note, we extends some of the results of Liu [Fuzzy Sets and systems 157 (2006) 869-878]. This extension consists of a simple proof involving weighted functions and their preference index. We also give an elementary simple proof of the maximum entropy weighting function problem with a given preference index value without using any advanced theory like variational principles or without using Lagrangian multiplier methods.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.991-997
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• 2006

Recently, Liu (2005) proposed a special type of weighting function under a given preference index level with the minimal variability similar to the minimal variability OWA operator weights problem proposed by Fuller and Majlender (2003). He solved this problem using a result of classical optimal control theory. In this note, we give a direct elementary proof of this problem without using any known results.

• Structural Engineering and Mechanics
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• v.21 no.3
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• pp.315-332
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• 2005

The Element-free Galerkin Method has become a very popular tool for the simulation of mechanical problems with moving boundaries. The internally applied Moving Least Squares interpolation uses in general Gaussian or cubic weighting functions and has compact support. Due to the approximative character of this interpolation the obtained shape functions do not fulfill the interpolation conditions, which causes additional numerical effort for the application of the boundary conditions. In this paper a new weighting function is presented, which was designed for meshless shape functions to fulfill these essential conditions with very high accuracy without any additional effort. Furthermore this interpolation gives much more stable results for varying size of the influence radius and for strongly distorted nodal arrangements than existing weighting function types.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.10
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• pp.727-732
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• 1988

In this paper, a parameter estimation method of linear systems with bounded output disturbances is studied. The bound of the disturbances is assumed to known Weighting factors are proposed to modify LS(Least Square) algorithm in the parameter estimation method. The conditions of weighting factors are given so that the estimation method has good convergence properties. This condition is more relaxed form than other known conditions. The compensation term in the estimation equations is represented by a function of the output prediction error and this function should lie in a specified region on x-y plane to satisfy these conditions of weighting factors. A set of weighting factor is selected and an algorithm is proposed using this set of weighting factor. The proposed algorithm is compared with another existing algorithm by simulation and its performance in parameter estimation id discussed.