• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.62-68
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• 2002

It is well known that the MDVR beamforming outperforms the conventional delay-sum beamformer in the sense of noise rejection and bearing resolution. However, the MDVR method requires long observation time to achieve high frequency resolution. The STMV method uses the steered covariance matrix of sensor data, so it has an ability to form an adaptive weight vector from a single time-series snapshot. But it uses the same weight vector across all frequencies. In this paper, we propose an SSMV method. The basic idea of the SSMV method is to decompose a full frequency band into several subbands to acquire a weight vector for each subband, individually. Also the wrap may be divided into several subarrays in order to reduce a computational load and the bandwidth of each subband. Simulations using real sea trial data show that the proposed SSMV method has good performance with short observation time.

• The Journal of the Acoustical Society of Korea
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• v.23 no.8
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• pp.570-575
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• 2004

In the underwater acoustic systems. we can receive signals and retrieve information about a target by using a beamforming method. The most important thing in the beamforming is finding the way to optimize the mainlobe beamwidth and the sidelobe level to the desired value. One of the prominent results of beamforming method. which has been studied. is Philip's weighting function method(1) . Philip's method adaptively adjusts its weights of array to meet the desired mainlobe beamwidth and sidelobe level. It is very similar to the design method in adaptive filter. However. this method cannot easily bring us to the desired sidelobe level due to complementary relation between mainlobe beamwidth and sidelobe level. In this paper, we propose a new algorithm using partial constrained adaptation. This method makes us circumvent the above problem and meet the specification of design easily. The proposed algorithm presents a Pattern synthesis that designer can easily control the mainlobe beamwidth and the sidelobe level to the desired value while calculation time to converge is decreasing.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.167-177
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• 2013

In this paper, a motion adaptive deinterlacing algorithm is proposed. It consists of three parts: (1) modified edge-based line average, (2) pixel-based consequent five-field motion detection, and (3) block-based local characteristic for detecting true motion and calculating the motion intensity by using an improved method which is able to detect the inner part of moving objects precisely as well as to reduce the risk of false detection caused by intrinsic noises in the image. Depending on the detected motion activity level, it combines spatial and temporal methods with weighting factor. Simulations conducted on several video sequences indicate that the performance of the proposed method is superior to the conventional methods in terms of both subjective and objective video quality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.67-72
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• 2019

This paper evaluates the performance of CCA (Compact Constellation Algorithm) adaptive equalization algorithm by varying the step size for minimization of the distortion effect in the communication channel. The CCA combines the conventional DDA and RCA algorithm, it uses the constant modulus of the transmission signal and the considering the output of decision device by the power of compact slice weighting value in order to improving the initial convergence characteristics and the equalization noise by misadjustment in the steady state. In this process, the compact slice weight values were fixed, and the performance of CCA adaptive equalization algorithm was evaluated by the varing the three values of step size for adaptation. As a result of computer simulation, it shows that the smaller step size gives slow convergence speed, but gives excellent performance after at steady state. Especially in SER performance, the small step size gives more robustness that large values.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.197-203
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• 1997

In this paper, we present a GP-PID(Generalized Predictive PID) controller which has the same structure as a generalized predictive control with steady-state weighting. The proposed controller can perform better than the conventional PID controller because it includes intrinsic delay-time compensator. The PID tuning parameters and delay-time compensator are calculated by equating the two degree of freedom PID to a linear form of GPC. The proposed controller is combined with a supervisor for safe start and self-tuning. GP-PID controller has been tested for various numerical models and an experimental stirred tank heater. As a result, it was observed that the proposed controller shows a satisfactory performance for variable delay as well as stochastic disturbance.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.426-429
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• 1989

The robust self-tuning controller is designed which is guaranteed the asymptotic regulation and tracking in the presence of a bounded parameter perturbation. The global stability in the presence of a finite noise and disturbance is ensured. The controller has a error driven structure, and involves the common model of a disturbance and reference input in the internal model. The adaptive system tunes the controller parameters such that the quadratic performance index which involves a weighting factor is optimized.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.653-655
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• 1999

카메라 영상을 통하여 무인 헬리콥터 동작을 추정하기 위해 적응형 가중치를 사용한 새로운 Ego-Motion을 검출 기법을 제안하였다. 무인 헬리콥터 동적 특성은 비선형이며, 심한 진동 발생으로 영상 번짐(blur) 현상이 나타나기 때문에 상관 값만을 고려한 정합 방법으로는 빈번히 오차가 발생한다. 본 논문에서는 가속도, 각 가속도 및 제어입력 값에 의한 위치 추정 값과 상관 값 및 에지 강도를 가중치에 의해 융합하여 정확한 Ego-Motion을 계산할 수 있는 기법을 제안하였다. 또한 무인 헬리콥터의 가속도, 각 가속도, 상하 속도에 따라서 영상의 번짐 정도가 달라 이들 같이 크면 위치오차에 가중을 크게 주고, 작으면 상관 값에 가중치를 적게 주는 적응형 가중치 결정 알고리즘을 적용하였다. 제안한 적응형 가중치 기법을 무인 헬리콥터에 실험한 결과 카메라에 포착된 영상에 의해 무인헬기의 동작을 정확히 추정 할 수 있었다.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.84-98
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• 1995

Network-based model were developed to predict short term future traffic volume based on current traffic, historical average, and upstream traffic. It is presumed that upstream traffic volume can be used to predict the downstream traffic in a specific time period. Three models were developed for traffic flow prediction; a combination of historical average and upstream traffic, a combination of current traffic and upstream traffic, and a combination of all three variables. The three models were evaluated using regression analysis. The third model is found to provide the best prediction for the analyzed data. In order to balance the variables appropriately according to the present traffic condition, a heuristic adaptive weighting system is devised based on the relationships between the beginning period of prediction and the previous periods. The developed models were applied to 15-minute freeway data obtained by regular induction loop detectors. The prediction models were shown to be capable of producing reliable and accurate forecasts under congested traffic condition. The prediction systems perform better in the 15-minute range than in the ranges of 30-to 45-minute. It is also found that the combined models usually produce more consistent forecasts than the historical average.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.70-75
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• 2015

With the development of communication technologies and smartphone, requirements of positioning accuracy for LBS (Location Based Service) are becoming increasingly important. LBS is a service which offers the information or entertainment based on a location to users. Therefore, positioning is very important for LBS. Among many positioning methods, IEEE 802.11 WLAN positioning measures the distance using the RSSI (Received Signal Strength Indicator) attenuation log model. Thus in order to enhance positioning, we modify the IEEE 802.11 RSSI attenuation log model by adaptive weighting method. In this paper, we propose improved IEEE 802.11 RSSI attenuation log model for enhanced indoor positioning.

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.5
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• pp.63-70
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• 1993

In 1980's to 1990's the marine propulsion diesel engines have been developed into lower speed and longer stroke for the energy saving(small S.F.O.C.). As these new trends the convetional mechnical-hydraulic governors were not adapted to the new requirements and the digital governors have been adopted in the marine use. The digital governors usually use the control algorithms such as the PID control, optimal control, adaptive control and etc. While the engine has delay time and parameter variations these control algorithms have difficulty in considering the stability and the robustness for the model uncertainty. In this study, the $H_{\infty}$ controller design method are applied to the speed control of the low speed marine diesel engine. By comparison the $H_{\infty}$ control results with the PID control results, the validity of the $H_{\infty}$ controller under the delay time and parameter variations is confirmed.