• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.22-30
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• 1993

In this paper, robust adaptive control algorithms which can be applied to unknown uncertain systems are suggested. Transform matrix for dividing states into "uncontrolled" states and "controlled" states and general searching procedure for the transform matrix which assign arbitrary n-1 eigen values for the uncontrolled subsystem of n-th orther single-input single-output systems of which state variables can be observable are also studied and utilized for the design of new-type controllers. We drived new-type control laws by using adaptive control theory and variable structure system and its stability is proved by using Lyapunov stability theory.

• Smart Structures and Systems
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• v.4 no.1
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• pp.47-66
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• 2008

The present work utilizes system identification technique for health monitoring of shear building, wherein Parametric State Space modeling has been adopted. The method requires input excitation to the structure and also output acceleration responses of both undamaged and damaged structure obtained from numerically simulated model. Modal parameters like eigen frequencies and eigen vectors have been extracted from the State Space model after introducing appropriate transformation. Least square technique has been utilized for the evaluation of the stiffness matrix after having obtained the modal matrix for the entire structure. Highly accurate values of stiffness of the structure could be evaluated corresponding to both the undamaged as well as damaged state of a structure, while considering noise in the simulated output response analogous to real time scenario. The damaged floor could also be located very conveniently and accurately by this adopted strategy. This method of damage detection can be applied in case of output acceleration responses recorded by sensors from the actual structure. Further, in case of even limited availability of sensors along the height of a multi-storeyed building, the methodology could yield very accurate information related to structural stiffness.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.609-618
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• 2013

This paper proposes a fast image segmentation method that gives high segmentation performance as graph-cut based methods. Graph-cut based image segmentation methods show high segmentation performance, however, the computational complexity is high to solve a computationally-intensive eigen-system. This is because solving eigen-system depends on the size of square matrix obtained from similarities between all pairs of pixels in the input image. Therefore, the proposed method uses the small-size square matrix, which is obtained from all the similarities among regions obtained by segmenting locally an image into several regions by graph-based method. Experimental results show that the proposed multi-scale image segmentation method using the algebraic multi-grid shows higher performance than existing methods.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.760-765
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• 1992

In this paper, robust adaptive control algorithms which can be applied to unknown uncertain systems are suggested. Transform matrix for dividing states into "uncontrolled" states and "controlled" states and general searching procedure for the transform matrix which assign arbitrary n-1 eigen values for the uncontrolled subsystem of n-th order single-input single-output systems is also studied and utilized for the design of new-type controllers. We derived new-type control laws by using adaptive control theory and variable structure system and its stability is proved by using Lyapunov stability theory. From computer simulation results, we can see that the proposed adaptive control algorithm is robust and stable.s robust and stable.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1239-1246
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• 1999

This paper presents a new algorithm to construct the modular network model for SSR analysis by simply applying KCL to each node and KVL to all branches connected to the node sequentially. This method has advantages that the model can be derived directly from the system data for transient stability study and turbine/generator shaft model, the resulted model in the form of augmented state matrix is very sparse, and thus efficient SSR study of a large scale system becomes possible. The proposed algorithm is verified with the IEEE First and Second Benchmark models.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1042-1045
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• 1999

This paper presents a new method for contingency selection of the transient stability. Contingency ranking in transient stability is done by estimating the change in the imaginary part of electro-mechanical oscillation mode, which represents modal synchronizing coefficient. And the change in the imaginary part is obtained by applying eigen-sensitivity theory of augmented matrix to linear system model. The Proposed algorithm was tested for New England System and compared the results with PSS/E dynamic simulation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.363-373
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• 1995

In this study, a FE model tuning method using experimental modal data was suggested after examining all the published conventional methods. The idea of this method is introducing scale factors to maintain both the structural connectivity and the consistency in the corrected stiffness matrix which makes it always possible to interpret the stiffness elements with the corresponding physical configuration of the targeting structure. The scale factors are determined to minimize the objective function of eigen-properties. The proposed method was tested to determine the joint stiffness of a T shaped beam. The test results were also compared with the tuned stiffness obtained from a probed commercial package (SYSTUNE) and found that this method is very accurate and compatible.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.105-111
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• 1995

This paper proposes a segmentation algorithm using gray-level discontinuity and surface reflectance ratio of input images obtained under different illumination conditions. Each image is divided by a certain number of subregions based on the thresholds. The thresholds are determined using the histogram of fusion image which is obtained by ANDing the multiple input images. The subregions of images are projected on the eigenspace where their bases are the major eigenvectors of image matrix. Points in the eigenspace are classified into two clusters. Images associated with the bigger cluster are fused by revised ANDing to form a combined edge image. Missing edges are detected using surface reflectance ration and chain code. The proposed algorithm obtains more accurate edge information and allows to more efficiently recognize the environment under various illumination conditions.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.892-894
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• 2005

Graph partitioning provides an important tool for data clustering, but is an NP-hard combinatorial optimization problem. Spectral clustering where the clustering is performed by the eigen-decomposition of an affinity matrix [1,2]. This is a popular way of solving the graph partitioning problem. On the other hand, semidefinite relaxation, is an alternative way of relaxing combinatorial optimization. issuing to a convex optimization[4]. In this paper we present a semidefinite programming (SDP) approach to graph equi-partitioning for clustering and then we use eigen-decomposition to obtain an optimal partition set. Therefore, the method is referred to as semidefinite spectral clustering (SSC). Numerical experiments with several artificial and real data sets, demonstrate the useful behavior of our SSC. compared to existing spectral clustering methods.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.153-158
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• 2020

In this paper, we studied an algorithm for estimating a desired target by removing noise and interference in a wireless communication environment. When an information signal with a mixture noise and interference receive a receiver, noise and interference signals must be removed to accurately estimate a desired target. In order to divide the received signal region into two spatial, a power spectrum is obtained by analyzing a correlation matrix, covariance, eigen vector, and eigen value. The proposed spectrum is an algorithm that can remove noise and interference, and analyzes the existing algorithm and target estimation performance through simulation. As a result of simulation, the target estimation resolution of existing algorithm is more than 10°, but the resolution of the proposed algorithm is less than 10°. The proposed algorithm has improved the resolution of about 5° than the exiting algorithm. The proposed algorithm proved that the target estimation accuracy and resolution are superior to the existing algorithm.