• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.203-213
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• 2017

We study estimation and inference of joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. We consider a class of time-varying transformation models and combine the two marginal models using Gaussian copulas to estimate the joint models. Our models and estimation method can be applied in many situations where the conditional mean-based models are inadequate. Gaussian copulas combined with time-varying transformation models may allow convenient and easy-to-interpret modeling for the joint conditional distributions for bivariate longitudinal data. We apply our method to an epidemiological study of repeatedly measured bivariate cholesterol data.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.99-108
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• 2003

This paper is concerned with the problem of designing a guaranteed cost state feedback controller for singular systems with time-varying delays. The sufficient condition for the existence of guaranteed cost controller, the controller design method, and the optimization problem to get the upper bound of guaranteed cost function are proposed by LMI(linear matrix inequality), singular value decomposition, Schur complements, and change of variables. Since the obtained sufficient conditions can be changed to LMI form, all solutions including controller gain and the upper bound of guaranteed cost function can be obtained simultaneously. Moreover, the proposed controller design method can be extended to the problem of robust guaranteed cost controller design method for singular systems with parameter uncertainties and time-varying delays. The validity of the proposed design algorithm is investigated through a numerical example.

• Journal of Korea Water Resources Association
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• v.52 no.11
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• pp.895-904
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• 2019

It has been well recognized that extreme rainfall process often features a nonstationary behavior, which may not be effectively modeled within a stationary frequency modeling framework. Moreover, extreme rainfall events are often described by a two (or more)-component mixture distribution which can be attributed to the distinct rainfall patterns associated with summer monsoons and tropical cyclones. In this perspective, this study explores a Mixture Distribution based Nonstationary Frequency (MDNF) model in a changing rainfall patterns within a Bayesian framework. Subsequently, the MDNF model can effectively account for the time-varying moments (e.g. location parameter) of the Gumbel distribution in a two (or more)-component mixture distribution. The performance of the MDNF model was evaluated by various statistical measures, compared with frequency model based on both stationary and nonstationary mixture distributions. A comparison of the results highlighted that the MDNF model substantially improved the overall performance, confirming the assumption that the extreme rainfall patterns might have a distinct nonstationarity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.382-385
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• 2007

본 논문에서는 다중 표적의 중첩이라는 상황에 대한 새로운 해결 방식을 소개한다. 비선형 표적의 위치와 속도에 대한 추적을 중심으로 표적과 비표적의 중첩이 일어나는 순간 이후 분리되었을 때 추적중인 표적을 지속적으로 유지할 수 있는 방법에 대해 이야기 하고자 한다. 이 논문에서 제안된 알고리즘은 예측 명중위치 개념과 최대 잡음수준을 이용한 칼만필터 기반의 적응 상호작용 다중모델 기법으로 측정된 위치값과 예측된 명중위치 사이의 차이를 고려한 변형된 칼만필터 개념을 이용한다. 이 논문에서는 비선형 표적의 가속도를 시변 변수인 표적의 추가적인 잡음으로 두고 각각의 가속도 간격의 정도에 따라 얻어지는 모든 잡음에 대한 변수에 의해 각각의 하부 모델들을 특성화시켰다. 제안된 알고리즘은 표적의 운동특성에 따라 적응적으로 기법을 선택할 수 있는 선택적 방식을 구현하고자 한다. 표적의 기동중에 나타나는 가속도를 효과적으로 다루기 위하여 잡음의 크기가 급격히 증가하는 경우 그 증가분을 가속도로 인식하여 기동표적 관계식에 이용한다. 그리고 제안된 알고리즘의 수행 가능성을 보여주기 위하여 몇 가지 예를 제시하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.29-36
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• 2004

This paper deals with a fractional model reduction for linear systems with time varying delayed states. A contractive coprime factorization of linear time delayed systems is defined and obtained by solving linear matrix inequalities. Using generalize controllability and observability gramians of tile contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is illustrated.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.326-332
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• 2003

This paper deals with a model reduction for linear systems with time varying delayed states. A generalized controllability and observability gramians are defined and obtained by solving linear matrix inequalities. Using the generalized controllability and observability gramians, the balanced state space equation is realized. The reduced model can be obtained by truncating states in the balanced realization and the upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is performed.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.35-35
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• 2016

수문학적 빈도해석은 일반적으로 단변량 형태에 해석이 주를 이루고 있으나, 최근 다변량 해석에 대한 이해와 더불어, 해석 기술 발달에 따라 빈도해석에서도 다변량 해석적 접근이 이루어지고 있다. 기존 다변량 해석 방법으로는 Copula방법 적용이 활발하게 이루어지고 있으며, 특히 가뭄해석에 있어 지속시간과 심도를 동시에 평가하는 2변량 가뭄빈도해석에 대한 연구가 다수 이루어지고 있다. 그러나 기존 해석 방법은 정상성 해석 모형으로서 기상변동성과 같은 시변동성을 고려하는데 한계가 있다. 이러한 점에서 본 연구에서는 Bayesian 기반 Copula 함수의 매개변수를 추정함과 동시에 매개변수의 불확실성을 평가할 수 있는 2변량 비정상성 빈도해석 모형을 개발하였다. 본 연구에서는 최근 우리나라와 미국에서 발생한 2013-15년 가뭄빈도에 대한 평가와 동시에 이에 따른 불확실성을 정량적으로 평가하는 연구를 진행하였다.

• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.689-699
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• 2000

This paper presents the integrated storage function model (ISFM) to improve the accuracy of the storage function model (SFM) which is widely employed for flood runoff analysis and its forecasting in Korea. In order to achieve this objective, the optimization method is applied for estimation of parameters of the model which dominate the accuracy of the analysis, which is usually taken by empirical formulae, and they are treated as time dependent variables. The fuzzy control technique is used to detennine the time variant parameters. In addition, the ISFM can be applied to the combined routing of the watershed and the channel with a residual watershed.ershed.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.494-510
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• 2019

Underwater acoustic communication channel parameters consist of impulse response, delay spreading, scattering function, coherence bandwidth, frequency selective fading, coherence time and time variant magnitude fading statistics on which communication system modem and channel coding are designed. These parameters are influenced by sound velocity profile, platform motion and sea surface roughness in given acoustical oceanography condition. In this paper, channel model based on phasor, channel simulator, measurement and analysis method of channel parameters are given in a fixed source-to-receiver system and the parameters are analyzed using shallow water experimental data. For two different source-to-receiver ranges of 300 m and 600 m, the parameters are characterized by three multipaths such as a direct, a surface reflection path with time variant scattering and a bottom reflection path. The results present a channel modelling method of a fixed source source-to-receiver system, channel parameters measurement and analysis methods and a system design and performance assessment method in shallow water.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.73-81
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• 2001

This study uses the distributed parameter systems resented by the spatial discretization technique. In this paper, the distributed parameter systems are converted into lumped parameter systems, End fast Walsh transform and the Picard's iteration method are allied to analysis the state of the systems. This thesis presents a new algorithm which usefully exercises the optimal contro1 in the distributed parameter systems. In exercising the optimal control of the distributed parameter systems, the excellent consequences are found without using the existing decentralized contro1 or hierarchical control method. This study can be applied to the linear time-varying systems and the non-linear systems. Farther researches are required to solve the problems of convergence in case of the numerous applicable intervals. The simulation proves the effectiveness of the proposed algorithm.