• Journal of the Korean Chemical Society
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• v.35 no.6
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• pp.713-719
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• 1991

Electrochemical impedance measurement system using Fourier transform was constructed in the range of the frequencies up to 100 kHz. This system consists of pseudo-random noise generator, specially designed potentiostat, fast data acquisition system, system controller, and computer interface. The performance of the constructed system was found to be almost same as the commercially available system using lock-in amplifier. Measuring time was significantly reduced because the minimum time for the measurement depended on one cycle of the lowest frequency used. It would be possible to study time-varying electrochemical impedance systems such as the initial stages of corrosion processes using this system.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.1-10
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• 2012

The linear and decision-feedback equalization can mitigate time-varying intersymbol interference (ISI) caused by time-varying multipath propagation for underwater acoustic channels. The perfect elimination of interference components, however, is difficult using the linear equalization and the decision feedback equalizer has an error propagation problem. To overcome these shortcomings, this paper proposes an equalizer mode selection method using training sequences. The proposed method selects an equalization mode corresponding to the signal-to-noise ratio (SNR). If the SNR is low, the proposed system operates the linear equalizer for preventing the error propagation and if the SNR is high, the decision feedback equalizer for eliminating the residual ISI. Therefore, the proposed method can improve the error performance compared to the conventional equalizers. The computer simulation shows the proposed method improves the bit error performance using practical underwater channels responses acquired from the sea experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.552-555
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• 1997

Recently, increasing attention has been paid to the application of learning control method to robot manipulator control. Because the learning control method does not require an exact dynamic model, it is flexible and easy to implement. In this paper, we implement a learning control scheme which consists of a unique feedforward learning controller and a linear feedback controller. The learning control method does not require acceleration terms that are sensitive to noise and has the capability of rejecting unknown disturbances and adapting itself to time-varying system parameters. The feasibility of the learning control scheme is soon by implementing the control scheme to a commercial robot manipulator and the performance of which is also compared with the conventional linear PID control method.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.246-248
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• 2004

In this paper, we propose an optimal power control algorithm for CDMA cellular systems. The proposed power control algorithm is based on linear quadratic control theory. As the cellular system includes the changeability of system environment or various noise, Kalman filter is adapted to estimate the time-varying interference. This is the well-known linear quadratic Gaussian (LQG) theory. Through this algorithm, power transmission of each mobile with optimal one is more realistic. Simulation results show a fast convergence rate to optimal power value, and a rapid decreasing outage probability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.4
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• pp.753-761
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• 1998

The determination of sound pressure radiated from periodic plate structures is fundamental in the estimation of noise level in aircraft fuselages or ship hull structures. As a robust approach to this problem, here a very general and comprehensive analytical model is developed for predicting the sound radiated by a vibrating plate stiffened by periodically spaced orthogonal unsymmetrical beams subjected to a sinusoidally time varying point load. The plate is assumed to be infinite in extent, and the beams are considered to exert both line force and moment reactions on it. Using this theoretical model, the sound pressure levels on axis in a semi-infinited fluid (water) bounded by the plate were calculated using three numerical tools such as the Gauss-Jordan method, the LU decomposition method and the IMSL numberial package. Especially, the variation in the sound pressure levels and their modes were investigated according to the change in frequency, bay spacing and bay distance.

• Journal of KSNVE
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• v.5 no.3
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• pp.385-394
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• 1995

Recently, since robot manipulator becomes faster and lighter, its link is no longer regarded as rigid body, and robot controller which only controls robot position cannot reduce vibration of the flexible link. Therefore vibration control is needed in robot manipulator control in addition to position control. In the case that tip mass changes when robot manipulator in working, it is clear that the efficiency of the vibration/position controller designed for the fixed system goes down. In this paper, the system with time varying parameters, adaptive control theory is adopted which estimates parameters changed by the variation of the tip mass and re-calculates the gain of the controller. Validify of the proposed adaptive controller and capability of the estimator are evaluated by computer simulations and experiments. Comparison results of the optimal controller for the fixed system and proposed adaptive controller and carried out.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.165-168
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• 1998

본 논문에서는 충격성 잡음에 강인하기 위한 시변 주파수 추정 기법을 제안하였다 충격성 잡음에 강인하기 위해서는 충격성 잡음에 의한 추정 변수의 동요를 제한하고 추정된 오차가 향후 추정시 영향을 미치는 오차의 전파현상을 제한하여야 한다. 충격성 잡음에 의한 추정오차의 전파를 제한하기 위해서는 망각인자의 도입이 필요함을 증명하였고 보다 효과적으로 사용하기 위해서 가변 망각인자를 도입하였다. 가변 망각인자의 도입으로 충격성 잡음에 의한 오차의 전파를 선택적으로 제한할 수 있으며 충격성 잡음에 의한 추정계수의 변동은 영향함수 측면에서 Huber함수를 이용하여 제한하였다. 제안된 알고리듬은 Huber함수와 가변망각인자의 도입으로 충격성 잡음에 의해 생기는 오차의 크기와 오차의 영향이 전파되는 것을 적응적으로 제한하기 때문에 모의실험을 통해 기존의 칼만 알고리듬보다 나은 성능을 보임을 알 수 있었다.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.314-320
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• 2012

This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.89-97
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• 1997

To extract time-varying evoked potential (EP), segement latency corrected average method is presented. This method is composed of three steps. First, adaptive filtering for reducing the effect of artifacts and removing background noise is performed. Next, validated intervals of individual segments are aligned, and latency components are detected by cross-correlation between the previously obtained and measured EPs within the intervals. Finally, after the detected latency component, responses of segments are groupe and averaged, the shole corrected EP signal is obtained. In the experiments, the resutls of the conventional methods including simple averaging, Woody's method, and peak component latency corrected averaging are obtained, the results compared with the present method for evaluating performance. Therefore, the presented method confirms that it reflects the latency variations of fundamental peaks and gets the improved EP.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.127-144
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• 2006

The K-means algorithm is widely used at the initial stage of data analysis in data mining process, partly because of its low time complexity and the simplicity of practical implementation. Cluster validity indices are used along with the algorithm in order to determine the number of clusters as well as the clustering results of datasets. In this paper, we present a performance comparison of sixteen indices, which are selected from forty indices in literature, while considering their applicability to nonhierarchical clustering algorithms. Data sets used in the experiment are generated based on multivariate normal distribution. In particular, four error types including standardization, outlier generation, error perturbation, and noise dimension addition are considered in the comparison. Through the experiment the effects of varying number of points, attributes, and clusters on the performance are analyzed. The result of the simulation experiment shows that Calinski and Harabasz index performs the best through the all datasets and that Davis and Bouldin index becomes a strong competitor as the number of points increases in dataset.