• 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.

• 대한전기학회논문지
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• 제37권3호
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• pp.180-185
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• 1988

This paper considers the problem of the optimal input design for parameter estimtion in the ARMAX model in which the system and noise transfer function have the common denominator polynomial. Deriving the information matrix, in detail, for the assumed model structure and using the autocorrelation functin of the filtered input as design variables, it is shown that D-optimal input signal can be realized as an autoregressive moving average process. Computer simulations are carried out to show the standard-deviation reduction in the parameter estimtes using the optimal input signal.

• 대한전기학회논문지
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• 제38권2호
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• pp.127-136
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• 1989

This paper describes the parameter convergence properties of an adaptive system to identify a single-input single-output plant model. It is demonstrated that, by using power spectrum analysis, the persistency of excitation (PE) condition in order to guarantee the exponential stability of the adaptive control system can be transformed into the positive definite behavior for the auto-correlation function matrix of adaptive signal. The existence of parameter nominal values can be analyzed by this condition and the convergence rates of parameter are determined by examining the auto-correlation function. We may use the sufficient richness (SR) of input spectrum instead of the PE condition to analyze the parameter boundedness. It can be shown that the eigen values of the auto-correlation function are always related with adaptive gain, input amplitude and positions or numbers of input spectra. In each case, the variation of parameter convergence rate can be also verified.

• 전자공학회논문지
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• 제51권12호
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• pp.59-65
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• 2014

다양한 게이트 핑거 수(Nf)의 MOSFET에 대한 두 종류의 입력 저항이 $S_{11}$-parameter와 $Z_{11}$-parameter으로부터 변환 되어 저주파 영역에서 측정되었다. 본 연구에서 사용된 $Nf{\leq}64$의 범위에서 $S_{11}$-parameter로부터 추출된 1/Nf 종속 입력저항은 $Z_{11}$-parameter로부터 추출된 입력 저항보다 훨씬 낮은 값을 보여주며, 이러한 1/Nf 종속성은 MOSFET의 등가회로로부터 유도된 Nf 종속 비선형 방정식으로부터 이론적으로 증명하였다.

• 전자공학회논문지
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• 제53권12호
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• pp.15-19
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• 2016

매우 큰 사이즈를 가진 multi-finger RF MOSFET의 $S_{11}$-parameter에서 스미스차트의 저항 circle 라인을 벗어나는 kink 현상의 게이트 바이어스 종속 특성이 관찰되었다. 이러한 바이어스 종속성은 $S_{11}$-parameter의 크기와 위상, 입력저항, 입력 커패시턴스의 주파수 응답곡선을 측정하여 최초로 분석되었다. 그 결과 입력 커패시턴스의 크기와 입력저항의 dominant pole과 zero 주파수에 의해 $V_{gs}$ 종속 kink 현상이 크게 변하는 것을 알 수 있다. $V_{gs}=0V$일 때 매우 적은 $S_{11}$-parameter 위상차와 입력저항의 높은 pole 주파수에 의해 고주파영역에서 kink 현상이 나타난다. 하지만 $V_{gs}$가 높아지면 $S_{11}$-parameter 위상차가 크게 증가하고 pole 주파수가 낮아져 저주파영역에서 kink 현상이 발생하게 된다.

• 한국경영과학회지
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• 제42권2호
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• pp.35-48
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• 2017

As the technology convergence paradigm emerges, the need for "CIA techniques" to analyze the mutual effects of technology is increasing. However, since the CIA input parameter estimation is difficult, the present study suggests a "CIA input parameter setting model" to alleviate the difficulty of CIA input parameter estimation. This paper is focused on the difference of measurement difficulty by each scale which expert's estimation behavior was defined as measurement activity quantifying the judgment of future technology. Therefore, this model is designed to estimate the input variable as a sequence or isometric scale that is relatively easy to measure, and then converts it into a probability value. The input parameter setting model of the CIA technique consists of three sub-models : 'probability value derivation model', 'influence estimation model', and 'impact value calculation model', in order to develop a series of models the Thurstone V model, Regression Analysis, etc has been used.

• 대한전기학회논문지:전력기술부문A
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• 제48권4호
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• pp.410-418
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• 1999

This paper describes the use of residual and parameter identification methods for fault detection in an air handling unit. Faults can be detected by comparing expected condition with the measured faulty data using residuals. Faults can also be detected by examining unmeasurable parameter changes in a model of a controlled system using a system identification technique. In this study, AutoRegressive Moving Average with seXtrnal input(ARMAX) and AutoRegressive with eXternal input(ARX) models with both single-input/single-input and multi-input/single-input structures are examined. Model parameters are determined using the Kalman filter recursive identification method. Regression equations are calculated from normal experimental data and are used to compute expected operating variables. These approaches are tested using experimental data from a laboratory's variable-air-volume air-handling-unit.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1655-1658
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• 1991

This paper considers the design and analysis of one-step ahead optimal and adaptive controllers, under the restriction that a known constraint on the input amplitude is imposed. It is assumed that the discrete-time single-input, single-output system to be controlled is linear, except for inequality constraints on the input. The objective function to be minimized is an one-step quadratic function, where polynomial weights on the input and output are included. Both the known parameter and unknown parameter (indirect adaptive controller) cases are examined.

• 대한산업공학회지
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• 제27권1호
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• pp.47-53
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• 2001

In this paper, we compare the classification performances of both ensemble and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. In view of the unknown relationship between input and output function, we use a Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: When the level of the variance is medium, Bagging & Parameter Combining performs worse than Logistic Regression, Variable Selection Bagging and Clustering. However, classification performances of Logistic Regression, Variable Selection Bagging, Bagging and Clustering are not significantly different when the variance of input data is either small or large. When there is strong correlation in input variables, Variable Selection Bagging outperforms both Logistic Regression and Parameter combining. In general, Parameter Combining algorithm appears to be the worst at our disappointment.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(2)
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• pp.245-248
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• 2000

In this paper, we present a high-performance SiGe HBT's RF input impedance parameter extraction method. The SiGe HBT has emitter width of 0.5${\mu}{\textrm}{m}$ and length of 6${\mu}{\textrm}{m}$. S-parameter has been measured with the collector current of 1~3㎃ using on-wafer RF measuring system . The pre-calculation method was used in order to overcome the local minimum problem. This method enabled us to extract a RF(1~10㎓) input impedance parameter.