• The Journal of the Acoustical Society of Korea
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• v.13 no.3
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• pp.71-77
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• 1994

The frequency characteristics of sound radiated by a line array of bubbles in water was investigated theoretically and experimentally. In the theory we proposed an effective coupled harmonic oscillator model for a line array of bubbles treating the interaction of only adjacent bubbles as the coupling of classical harmonic oscillators. For weak coupling of bubbles that the distance between adjacent bubbles is larger than the diameter of a bubble, the pressented theoretical model shows very good agreement with the experimental results.

• Progress in Medical Physics
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• v.2 no.2
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• pp.175-182
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• 1991

A newly derived O$_2$ Saturation Model which can be adapted to the design and study of Artificial Lung and Blood Gas Calculator etc. is introduced on the basis of Electrical Equivalent Circuits. The presented 4 stage and 2 stage RC circuits have good correlatons with actual chemical reactions of Hemoglobin and Oxygen. However, from results of computer simulations, 2 stage equivalent model is more accurate than 4 stage and conventional O$_2$ saturation models.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1781-1782
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• 2008

본 논문은 시간 지연을 가지는 이산 시간 비선형 상호 결합 시스템의 분산 퍼지 출력 궤환 제어기의 설계에 대해 연구한다. T-S(Takagi-Sugeno) 퍼지 모델 기법을 이용하여 퍼지 상호 결합 시스템을 구한다. 이를 바탕으로 분산 퍼지 출력 궤환 제어기를 설계하고, 폐루프 시스템의 안정도 충분 조건을 선형 행렬 부등식 (LMI)의 형태로 나타낸다. 설계된 이득값을 통하여 상호 결합 시스템이 안정화됨을 모의실험을 통하여 보인다.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.229-234
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• 1996

로우버스트 추정에서 자주 사용되는 Huber의 ${\phi}$-함수의 선형 결합을 통해 새로운 재하강 ${\phi}$-함수를 도출한다. 이 함수를 사용하면 적절한 조건하에서 앞의 두 함수를 사용할 때보다 위치 모수(location parameter)에 대한 추정량의 점근분산(asymptotic variance)을 감소시킬 수 있음을 보였다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.7 no.4
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• pp.1-5
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• 1970

This presents the way in shich the input impedance, and the output waveform of the line discriminator are influenced by a discrepancy of less than $\pm$10% in the coupling resistor resistance from the optium value(Characteristic impedance of the transmission line used in the line discriminator)

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.1-10
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• 2022

Deep neural networks are widely used to solve various problems. In a fully connected neural network, the nonlinear activation function is a function that nonlinearly transforms the input value and outputs it. The nonlinear activation function plays an important role in solving the nonlinear problem, and various nonlinear activation functions have been studied. In this study, we propose a combined parametric activation function that can improve the performance of a fully connected neural network. Combined parametric activation functions can be created by simply adding parametric activation functions. The parametric activation function is a function that can be optimized in the direction of minimizing the loss function by applying a parameter that converts the scale and location of the activation function according to the input data. By combining the parametric activation functions, more diverse nonlinear intervals can be created, and the parameters of the parametric activation functions can be optimized in the direction of minimizing the loss function. The performance of the combined parametric activation function was tested through the MNIST classification problem and the Fashion MNIST classification problem, and as a result, it was confirmed that it has better performance than the existing nonlinear activation function and parametric activation function.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.423-429
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• 2011

This paper deals with the observer-based decentralized fuzzy controller design for nonlinear interconnected system for PEMFC. The nonlinear interconnected system is represented by a Takagi-Sugeno (T-S) fuzzy model. Based on T-S fuzzy interconnected system, the fuzzy observer and the decentralized fuzzy controller are designed. The stability condition of the closed-loop system with the proposed controller is represented to the linear matrix inequality (LMI) form, and the observer and control gain s are obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.5
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• pp.278-293
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• 2019

The joint distribution of wave height and period has been maltreated despite of its great engineering value due to the absence of any analytical model for wave period, and as a result, no consensus has been reached about the effect of nonlinearity on these joint distribution. On the other hand, there was a great deal of efforts to study the effects of non-linearity on the wave height distribution over the last decades, and big strides has been made. However, these achievements has not been extended to the joint distribution of wave height and period. In this rationale, we first express the joint distribution of wave height and period as the product of the marginal distribution of wave heights with the conditional distribution of associated periods, and proceed to derive the joint distribution of wave heights and periods utilizing the models of Longuet-Higgins (1975, 1983), and Cavanie et al. (1976) for conditional distribution of wave periods, and height distribution derived in this study. The verification was carried out using numerically simulated data based on the Wallops spectrum, and the nonlinear wave data obtained via the numerical simulation of random waves approaching toward the uniform beach of 1:15 slope. It turns out that the joint distribution based on the height distribution for finite banded nonlinear waves, and Cavanie et al.'s model (1976) is most promising.

• The Korean Journal of Financial Management
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• v.17 no.1
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• pp.161-180
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• 2000

본 연구는 주가를 예측하는데 있어서 선형 회귀모형을 이용하는 방법과 비선형 인공신경망 모형을 이용하는 방법을 비교 분석하여, 어떤 모형이 더 우수한 예측성과를 내는지를 검증한다. 자본시장에서 투자자들은 접근하는 정보가 다르고 각기 상이한 예측 변수들을 토대로 나름대로의 예측치를 만들어 낸다. 이렇게 볼 때 개별 투자자들이 이용하는 다양한 정보집합을 결합하여 단일의 뛰어난 정보집합을 만들어내는 것은 매우 어려운 과제이다. 따라서 본 연구에서는 이용 가능한 소수의 예측 변수들을 어떤 방식으로 결합하는 것이 예측오차의 분산을 최소화할 수 있는지에 대한 현실적인 접근방법을 모색하고자 한다. 거시경제변수나 시장자료를 입력변수로 사용한 기존 연구와는 달리 본 연구에서는 재무제표 정보를 입력변수로 사용하였다 즉, 대차대조표의 최종요약치인 주당 지분의 장부가치와 손익계산서의 최종요약치인 주당 순이익을 입력변수로 사용했으며 1991년부터 1995년까지의 추정(학습)결과를 토대로 모형을 선택하여 1996년의 제무제표 정보로 1997년의 주가를 예측하는 것이 본 연구의 과제이다. 연구결과, 대체로 선형회귀모형에 비해 비선형 신경망 모형이 예측오차의 분산을 감소시키는 것으로 나타났다.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.545-554
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• 2006

We suggest a method for generating multidimensional random tables based on the log-linear models. A linear combination approach by Lee(1997) is applied to get the joint distribution with the well known Pearson chi-squared statistics. We can generate completely associated joint distributions which have the fixed association among three variables by using the suggested method. Therefore the method can be extended to more higher dimension than the three dimensional tables.