• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.121-124
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• 2000

적응 학습 알고리즘으로 가중치를 변화시키는 단층 신경망의 출력부에 Ramp 임계 함수를 적용하여 입력이 zero-mean Gaussian random vector인 경우 가중치의 stationary point를 구하고, 적응 학습 알고리즘을 유도한다.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2031-2042
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• 2017

In this paper, a novel traffic flow control method based-on ramp metering and speed regulation using an adaptive sliding mode control (ASMC) method along with a deadzoned parameter adaptation law is proposed at a stochastic macroscopic level traffic environment, where the influence of the density and speed disturbances is accounted for in the traffic dynamic equations. The goal of this paper is to design a local traffic flow controller using both ramp metering and speed regulation based on ASMC, in order to achieve the desired density and speed for the maintenance of the maximum mainline throughput against disturbances in practice. The proposed method is advantageous in that it can improve the traffic flow performance compared to the traditional methods using only ramp metering, even in the presence of ramp storage limitation and disturbances. Moreover, a prior knowledge of disturbance magnitude is not required in the process of designing the controller unlike the conventional sliding mode controller. A stability analysis is presented to show that the traffic system under the proposed traffic flow control method is guaranteed to be uniformly bounded and its ultimate bound can be adjusted to be sufficiently small in terms of deadzone. The validity of the proposed method is demonstrated under different traffic situations (i.e., different initial traffic status), in the sense that the proposed control method is capable of stabilizing traffic flow better than the previously well-known Asservissement Lineaire d'Entree Autoroutiere (ALINEA) strategy and also feedback linearization control (FLC) method.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.283-289
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• 2015

In this paper, a GNSS interference detection algorithm based on an adaptive fading Kalman filter is proposed to detect a spoofing signal which is one of the threatening GNSS intentional interferences. To detect and mitigate the spoofing signal, the fading factor of the filter is used as a detection parameter. For simulation, the effect of the spoofing signal is modeled by the ramp type bias error of the pseudorange to emulate a smart spoofer and the change of the fading factor value according to ramp type bias error is quantitatively analyzed. In addition, the detection threshold is established to detect the spoofing signal by analyzing the change of the error covariance and the effect of spoofing is mitigated by controlling the Kalman gain of the filter. To verify the performance analysis of the proposed algorithm, various simulations are implemented. Through the results of simulations, we confirmed that the proposed algorithm works well.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.186-191
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• 2011

Ramp metering has been used to solve recurrent or non-recurrent congestion on many highways. However, the existing ramp metering methods cannot control non-recurrent congestion like incident and don't have any methods to solve congestion after congestion. In addition, the methods cannot solve congestion quickly because ramp metering operates independently for each ramp. In this study, we developed SARAM which is ramp metering technique with shockwave theory in order to solve the problems. In simulation from Jangsoo IC to Joongdong IC, we confirmed that speed increased by 7.32km/h and delay time reduced by 39.14sec.

• Convergence Security Journal
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• v.8 no.4
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• pp.127-134
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• 2008

In this paper, we try to improve the accuracy of automatic measurement for analysis equipment by detecting efficiently the edge of a waterdrop with transparency. In order to detect the edge of a waterdrop with transparency, we use an edge detecting technique, MADD (Modified Adaptive Directional Derivative), which can identify the ramp edges with various widths as the perfectly sharp edges and respond effectively regardless of enlarging or reducing the image. The proposed edge detecting technique by means of perfect sharpening of ramp edges employs the modified adaptive directional derivatives instead of the usual local differential operators in order to detect the edges of image. The modified adaptive directional derivatives are defined by introducing the perfect sharpening map into the adaptive directional derivatives. Finally we apply the proposed method to contact angle arithmetic and show the effiency and validity of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.4
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• pp.78-83
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• 1984

A method is proposed for the adaptive control of linear time varying discrete systems. The stability problem of the model reference adaptive control systems is considered by means of the properties of hypergtability, The hyperstability approach also allows for solutions to the adaptation mechanism. Employing the principles of the continuous time case with output feedback renders it to the discrete case which simplified the system design. The system response is obtained by applying the ramp and step input as a reference signal to the system respectively. With checking the adaptation time for ramp and step input the validity of proposed algorithm was confirmed by the computer simulation.

• Convergence Security Journal
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• v.6 no.3
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• pp.29-35
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• 2006

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1119-1125
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• 1999

In this paper, a decentralized multilevel-adaptive controller for a boiler-turbine system is designed by using multiple model adaptive method. It is applied to the drum type boiler-turbine system which is simplified from Boryung T/P #1,2 model. A linearlized model is decomposed into three subsystems by means of linear transformation. Then the DMC based on such subsystem is designed and a Multiple Model Adaptive Control(MMAC) scheme is applied for the purpose of the good tracking to variable load demands of the thermal power plant. The good performance of the designed controller is shown by simulations in various conditions that have the large step and ramp change of power demamd.

• Convergence Security Journal
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• v.7 no.3
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• pp.39-44
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• 2007

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.961-970
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• 2007

Since the usual conventional edge detectors employ the local differential derivatives, the detected edges are not uniform in their widths or some edges are missed out of the detection on magnified images. We employ a mapping from the exactly monotonic intensity distributions of ramp edges to the simple step functions of intensity, which is referred to as perfect sharpening map of ramp edges. This map is based on the non-local feature of intensity distribution and used to introduce a modified differentiation, in terms of which we can construct an efficient edge detector adaptive to the variation of edge width. By adopting the operator MADD in this paper, we developed an edge detector that works stably against the magnification of image or the variation of edge width. It is shown by comparing to the conventional algorithms that the proposed one is very excellent.