• Journal of information and communication convergence engineering
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• 제15권2호
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• pp.73-78
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• 2017

A general linearly constrained broadband adaptive array is examined in the eigenvector space with respect to the optimal weight vector and the adaptive algorithm. The optimal weight vector and the general adaptive algorithm in the eigenvector space are obtained by eigenvector matrix transformation. Their operations are shown to be the same as in the standard coordinate system except for the relevant transformed vectors and matrices. The nulling performance of the general linearly constrained broadband adaptive array depends on the gain factor such that the constraint plane is shifted perpendicularly to the origin by an increase in the gain factor. The general linearly constrained broadband adaptive array is observed to perform better than a conventional linearly constrained adaptive array in a coherent signal environment, while the former performs similarly to the latter in a non-coherent signal environment.

• Journal of information and communication convergence engineering
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• 제15권3호
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• pp.137-142
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• 2017

A general linearly constrained narrowband adaptive array is examined in the eigenvector space. The optimum weight vector in the eigenvector space is shown to have the same performance as in the standard coordinate system, except that the input signal correlation matrix and look direction steering vector are replaced with the eigenvalue matrix and transformed steering vector. It is observed that the variation in gain factor results in the variation in the distance between the constraint plane and the origin in the translated weight vector space such that the increase in gain factor decreased the distance from the constraint plane to the origin, thus affecting the nulling performance. Simulation results showed that the general linearly constrained adaptive array performed better at an optimal gain factor compared with the conventional linearly constrained adaptive array in a coherent signal environment and the former showed similar performance as the latter in a noncoherent signal environment.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1264-1271
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• 1999

In this paper, an efficient method of analysis and design of fault detection filter is presented. Since the directional constraint is applied to the eigenstructure associated with the detection space, an eigenvector is determined by the eigenvalues associated with other eigenvectors. Further, the assignment of a pair of eigenvalue and eigenvector leads to the fixation of overall eigenstructure related with the detection space. Using the transmission zeros and the transmission zero vectors, these phenomenon are clearly proven, and an efficient algorithm for design of the fault detection filters is presented.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.958-964
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• 1999

The distance in load parameter space to the closest saddle node bifurcation (CSNB) point provides the worst case power margin to voltage instability and the left eigenvector at CSNB identifies the most effective direction to steer the system to maximize voltage stability under contingency. This paper presents an improved direct method for computing CSNB: the order of nonlinear systems equations is reduced to about twice of the size of load flow equations in contrast to about three-times in Dobson's direct method; the initial guess for the direct method is computed efficiently and robustly by combined use of continuation power flow, a pair of multiple load flow solution with Lagrange interpolation. It is also shown that voltage stability may be enhanced significantly with shift of generations in the direction of the left eigenvector at CSNB.

• 말소리와 음성과학
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• 제1권1호
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• pp.69-73
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• 2009

This paper proposes an efficient global covariance-based principal component analysis (GCPCA) for speaker identification. Principal component analysis (PCA) is a feature extraction method which reduces the dimension of the feature vectors and the correlation among the feature vectors by projecting the original feature space into a small subspace through a transformation. However, it requires a larger amount of training data when performing PCA to find the eigenvalue and eigenvector matrix using the full covariance matrix by each speaker. The proposed method first calculates the global covariance matrix using training data of all speakers. It then finds the eigenvalue matrix and the corresponding eigenvector matrix from the global covariance matrix. Compared to conventional PCA and Gaussian mixture model (GMM) methods, the proposed method shows better performance while requiring less storage space and complexity in speaker identification.

• 한국통신학회논문지
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• 제28권10C호
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• pp.949-957
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• 2003

본 논문은 이동통신 환경하에서 각도퍼짐(Angle Spread)이 증가하여도 우수한 성능을 유지하는 그래디언트 온-오프 빔형성 알고리즘을 제안한다. 제안된 방법은 수신 벡터신호의 자기상관행렬의 최대 고유치에 대응하는 고유벡터를 이용하되 상대적으로 큰 고유치에 대응하는 2개 고유벡터를 이용하여 다이버시티 이득을 얻음으로써 하나의 고유벡터 하나만 이용하는 방법[1]보다 우수한 성능을 나타난다. 본 제안된 방법을 IS-2000 1X신호환경에서 모의실험 결과 각도퍼짐이 증가하여도 기존의 하나의 고유벡터 하나를 사용하는 알고리즘보다 성능이 우수함을 확인 하였다.

• 대한인간공학회지
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• 제18권2호
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• pp.121-132
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• 1999

This paper investigates the methodology to develop a layout of the simulator for measuring and evaluating human sensibility. Since the simulator layout is different from general building layouts in that it is organized in order to communicate systematically between facilities, laboratories to evaluate human sensibility and equipments to support experiments in simulator, two approaches based on eigenvector and cut tree are applied to develop a simulator layout. Qualitative input data (relationship chart. space requirements for each laboratory and equipment) are obtained and transformed into quantitative data. The information obtained by two approaches provides several meaningful clues to generate the simulator layout. The simulator layout is presented based on the obtained information by two approaches. Extracted quantitative data by using eigenvector and cut tree are meaningful of generating the simulator layout.

• 교육녹색환경연구
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• 제2권1호
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• pp.69-79
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• 2002

This paper investigates the methodology to develop a layout of the simulator for measuring and evaluating human sensibility. Since the simulator layout is different from general building layouts in that it is organized in order to communicate systematically between facilities, laboratories to evaluate human sensibility and equipments to support experiments in simulator, two approaches based on eigenvector and cut tree are support to develop a simulator layout. Qualitative input data (relationship chart, space requirements for each laboratory and equipment) are obtained and transformed into quantitative data. The information obtained by two approaches provides several meaningful clues to generate the simulator layout. The simulator layout is presented based on the obtained information by two approaches. Extracted quantitative data by using eigenvector and cut tree are meaningful of generating the simulator layout.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.235-237
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• 1997

The distance in load parameter space to the closest voltage collapse point (CSNB) provides the worst case power margin and the left eigenvector identifies the most effective direction to steer the system to maximize voltage stability under contingency. This paper proposes a new generation redispatch algorithm, which uses left eigenvector at CSNB to enhance the voltage stability. A Newton method is used to detect CSNB point. Proposed method is applicable to the selection of appropriate reactive power compensation and load shedding point detection. But this paper make a point of voltage stability enhancement only with generation redispatch. The proposed method has been tested for Klos Kerner 11-bus system.

• 대한기계학회논문집A
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• 제28권11호
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• pp.1621-1628
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• 2004

This paper proposes a design methodology for the robust observer using the eigenstructure assignment in multi-output systems so that the observer is less sensitive to the ill-conditioning factors such as unknown initial estimation error, modeling error and measurement bias in transient and steady-state observer performance. The robustness of the observer can be achieved by selecting the desired eigenvector matrix to have a small condition number that guarantees the small upper bound of the estimation error. So the left singular vectors of the unitary matrix spanned by space of the achievable eigenvectors are selected as a desired eigenvectors. Also, this paper proposes how to select the desired eigenvector based on the measure of observability and designs the observer with small gain. An example of a spindle drive system is simulated to validate the robustness to the ill-conditioning factors in the observer performance.