• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.313-316
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• 1997

Two different issues, design of reduced-order robust model predictive control and input signal design for identification of a MIMO system, are addressed and design techniques based on singular value decomposition(SVD) of the pulse response circulant matrix(PRCM) are proposed. For this, we investigate the properties of the PRCM, which is a periodic approximation of a linear discrete-time system, and show its SVD represents the directional as well as the frequency decomposition of the system. Usefulness of the PRCM and effectiveness of the proposed design techniques are demonstrated through numerical examples.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.2
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• pp.121-135
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• 1999

This paper studies the problem of inverting minimal path sets to obtain minimal cut sets for complex system. We describe efficiency of inversion algorithm by the use of boolean algebra and we develop inclusion-exclusion algorithm and pivotal decomposition algorithm for reliability calculation of complex system. Several examples are illustrated and the computation speeds between the two algorithms are undertaken.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.55-60
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• 1986

Conditions for achieving noninteraction in nonlinear multivariable systems via the decomposition of state space are well established. The main contribution of this paper is to present a Standard Decomposed System (SDS). The SDS is similar to the decomposed system of Isidorl, Krener, Gori-Giorgi, and Monaco but has a finer structure. The finer structure parallels the one used by Gilbert for linear systems. A weaker form of noninteraction, based on input-output behaviour, is decoupling. Some connections between decomposition and decoupling are also established.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.11
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• pp.511-518
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• 1986

An algorithm for block-decomposition of a linear, time-invariant, discrete large-scale systems is presented, based upon the matrix sign function on Z-plane. The block-decomposition is performed by defining a reference circle, a circular stripe and projection operators. Simulation study shows that the presented algorithm is very useful for multivariable control system's analysis and design.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.3 no.3
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• pp.55-58
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• 1980

Today, L.P. model has often been used in solving economic and managemental phenomena. But in case of adopting L.P. model in dealing with practical economic and managemental problems there is a possibility that we have difficulties in solving these problems because of greatness of model size, cost for collecting data, cost for adjusting matrix, and etc. In this respect "Decomposition Algorithm for L.P." has been used in overcoming the difficulties above stated. In this paper therefore, I will try to introduce and them criticize Dantzig -Wolfe's "Decomposition Method" and Kornai - Liptak's "Two - Level Planning".ot;Two - Level Planning".uot;.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1141-1144
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• 1993

For the design of multivariable fuzzy control systems the decomposition of control rules is preferable since it alleviates the complexity of the problem. In some systems, however, inference error of the Gupta's decomposition method is inevitable because of its approximate nature. In this paper, we propose a new multivariable fuzzy controller with a coordinator which can reduce the inference error of the decomposition method by using an index of applicability.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1709-1718
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• 2021

The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.345-351
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• 2014

This paper presents pedestrian recognition to improve performance for vehicle safety system or surveillance system. Pedestrian detection method using HOG (Histograms of Oriented Gradients) has showed 90% recognition rate. But if someone takes a picture in the rain, the image may be distorted by rain streaks and recognition rate goes down by 62%. To solve this problem, we applied image decomposition method using MCA (Morphological Component Analysis). In this case, rain removal method improves recognition rate from 62% to 70%. However, it is difficult to apply conventional image decomposition method using MCA on vehicle safety system or surveillance system as conventional method is too slow for real-time system. To alleviate this issue, we propose a rain removal method by using low-pass filter and DCT (Discrete Cosine Transform). The DCT helps separate the image into rain components. The image is removed rain components by Butterworth filtering. Experimental results show that our method achieved 90% of recognition rate. In addition, the proposed method had accelerated processing time to 17.8ms which is acceptable for real-time system.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.95-102
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• 2001

Fuzzy system is capable of uniformly approximating any nonlinear function over compact input space. The applications of fuzzy system, however, have been primarily limited by the need for large number of fuzzy rules, in particular, for the high-order nonlinear system. In this paper, we propose the reconstruction methods of fuzzy systems, parallel type and cascade, based on the decomposition of some classes of high-order nonlinear functions. Using the both types appropriately, we can reduce the number of fuzzy rules geometrically. It can be applied to the fuzzy system that has an online adaptive structure. Two examples of adaptive fuzzy sliding mode control are shown in the computer simulations to verify the validity of the proposed algorithm.

• 한국해양학회지
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• v.28 no.4
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• pp.323-331
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• 1993

The concentration-dependence of and the effect of light on urea decomposition, and the suppression of urea decomposition by ammonium were studied to understand adaptations in phytoplankton to utilization of urea in the estuarine system of the Mankyung and Dongjin rivers and a hypertrophied pond. Results of size-fractionation showed that bacterial fraction played a minor role (14%) in urea decomposition in the estuary. However, the role of bacteria in urea decomposition seemed to increase in a hypertrophic pond. Natural phytoplankton communities exhibited a monophonic or biphasic kinetics of urea decomposition over a wide range of concentration (upto 7.7 mM). the addition of high concentration of ammonium and incubation of the euphotic samples in the dark caused reductions in the urea decomposition rates. It is suggested that understanding of adaptations in phytoplankton to urea decomposition would help to study the temporal and spatial variabilities of urea decomposition rates in the field and the significance of urea in nitrogen cycle.