• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.17-19
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• 2001

In this paper, eigenvalue perturbation theory and its applications for the augmented system matrix are described. This theory is quite useful in the cases where any change in a system parameter results in signifiant changes to most of the elements of the augmented matrix or where the forming of sensitivity matrix so complicate. And AMEP(augmented matrix eigenvalue perturbation) for the excitation system parameters are computed for analysis of small signal stability of KEPCO 215-machine 791-bus system.

• Nonlinear Functional Analysis and Applications
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• 제27권4호
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• pp.869-879
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• 2022

In this paper, we consider matrix optimization problems. We investigate augmented Lagrangian methods of multipliers and alternating direction methods of multipliers for the problems. Following the proofs of Eckstein [3], and Eckstein and Yao [5], we prove convergence theorems for augmented Lagrangian methods of multipliers and alternating direction methods of multipliers for the problems.

• 전기학회논문지
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• 제67권5호
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• pp.651-655
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• 2018

In this paper, based on an augmented Lyapunov-Krasovskii functional(LKF) with time-delay product quadratic terms, the stability result in the form of linear matrix inequality(LMI) is proposed. In getting an LMI result, the free matrix based integral inequality is used. Finally, two well-known numerical examples are given to demonstrate the usefulness of the proposed result.

• 응용통계연구
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• 제24권4호
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• pp.647-656
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• 2011

발생행렬은 블완비블럭계획법을 나타내는 좋은 도구이나 우리가 발생행렬을 이용하여 관심의 대상인 블완비블럭계획법이 균형불완비블럭계획법이 되는 지를 알기는 충분하지 않다. 그래서 필요한 수단이 구조행렬이다. 불완비블럭계획법을 평가하기 위한 또 다른 수단으로서 우리는 확장발생행렬과 ${\lambda}$행렬을 제안할 수 있다. 확장발생행렬과 ${\lambda}$행렬을 통하여 우리는 관심의 대상인 블완비블럭계획법이 균형불완비블럭계획법이 되는 지를 명확히 밝힐 수가 있고, 그 패턴도 상세히 파악할 수 있게 된다.

• ETRI Journal
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• 제40권4호
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• pp.499-510
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• 2018

A vector space based augmented structural kinematic (VSASK) feature descriptor is proposed for human activity recognition. An action descriptor is built by integrating the structural and kinematic properties of the actor using vector space based augmented matrix representation. Using the local or global information separately may not provide sufficient action characteristics. The proposed action descriptor combines both the local (pose) and global (position and velocity) features using augmented matrix schema and thereby increases the robustness of the descriptor. A multiclass support vector machine (SVM) is used to learn each action descriptor for the corresponding activity classification and understanding. The performance of the proposed descriptor is experimentally analyzed using the Weizmann and KTH datasets. The average recognition rate for the Weizmann and KTH datasets is 100% and 99.89%, respectively. The computational time for the proposed descriptor learning is 0.003 seconds, which is an improvement of approximately 1.4% over the existing methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.749-753
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• 1996

This paper presents a new method for first and second order eigen-sensitivity analysis of system matrix in augmented form. Eigen-sensitivity analysis provides invaluable informations in power system planning and operation. However, conventional eigen-sensitivity analysis methods, which need all the eigenvalues and eigenvectors, can not be applicable to large scale power systems due to large computer memory and computing time required. In the proposed method, all sensitivity computations for a mode are carried out using the augmented system matrix and its own eigenvalue and right & left eigenvectors. In other words sensitivity analysis for a mode does not need informations on the other eigenvalues and eigenvectors and sparsity technique can be fully utilized. Thus compuations can be done very efficiently with moderate computer memory and computing time even for large power systems. The proposed algorithm is tested for one machine infinite bus system.

• 전기학회논문지
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• 제60권3호
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• pp.620-624
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• 2011

This paper propose a new delay-dependent stability criterion of neutral time-delay systems. By employing double-integral terms in augmented states and constructing a new Lyapunov-Krasovskii's functional, a delay-dependent stability criterion is established in terms of Linear Matrix Inequality. Through numerical examples, the validity and improvement results obtained by applying the proposed stability criterion will be shown.

• 전기학회논문지
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• 제59권2호
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• pp.411-416
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• 2010

In this paper, an integral variable structure static output feedback controller with an integral-augmented sliding surface is designed for the improved robust control of a uncertain system under unmatched system uncertainty and matched input matrix uncertainty and disturbance satisfying some conditions. To effectively remove the reaching phase problems, an output dependent integral augmented sliding surface is proposed. Its equivalent control and ideal sliding mode dynamics are obtained. The previous some limitations is overcome in this systematic design. A stabilizing control with the closed loop exponential stability is designed for all unmatched system matrix uncertainties and proved together with the existence condition of the sliding mode on S=0. To show the usefulness of the algorithm, a design example and computer simulations are presented.

• 정보관리학회지
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• 제39권3호
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• pp.99-132
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• 2022

본 연구의 목적은 LDA 토픽모델링 결과와 BERTopic 토픽모델링 결과를 합성하는 방법론인 Augmented and Extended Topics(AET)를 제안하고, 이를 사용해 문헌정보학 분야의 연구주제를 분석하는 데 있다. AET의 실제 적용결과를 확인하기 위해 2001년 1월부터 2021년 10월까지의 Web of Science 내 문헌정보학 학술지 85종에 게재된 학술논문 서지 데이터 55,442건을 분석하였다. AET는 서로 다른 토픽모델링 결과의 관계를 WORD2VEC 기반 코사인 유사도 매트릭스로 구축하고, 매트릭스 내 의미적 관계가 유효한 범위 내에서 매트릭스 재정렬 및 분할 과정을 반복해 증강토픽(Augmented Topics, 이하 AT)을 추출한 뒤, 나머지 영역에서 코사인 유사도 평균값 순위와 BERTopic 토픽 규모 순위에 대한 조화평균을 통해 확장토픽(Extended Topics, 이하 ET)을 결정한다. 최적 표준으로 도출된 LDA 토픽모델링 결과와 AET 결과를 비교한 결과, AT는 LDA 토픽모델링 토픽을 한층 더 구체화하고 세분화하였으며 ET는 유효한 토픽을 발견하였다. AT(Augmented Topics)의 성능은 LDA 이상이었으며 ET(Extended Topics)는 일부 경우를 제외하고 대부분 LDA와 유사한 수준의 성능을 나타내었다.

• 제어로봇시스템학회논문지
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• 제20권2호
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• pp.170-174
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• 2014

In this paper, an unknown input estimation method via the optimal FIR smoother is proposed for linear discrete-time systems. The unknown inputs are represented by random walk processes and treated as auxiliary states in augmented state space models. In order to estimate augmented states which include unknown inputs, the optimal FIR smoother is applied to the augmented state space model. Since the optimal FIR smoother is unbiased and independent of any a priori information of the augmented state, the estimates of each unknown input are independent of the initial state and of other unknown inputs. Moreover, the proposed method can be applied to stochastic singular systems, since the optimal FIR smoother is derived without the assumption that the system matrix is nonsingular. A numerical example is given to show the performance of the proposed estimation method.