• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.758-760
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• 1995

The purpose of noise cancellation is to estimating signals corrupted by additive noise or interference. In this paper, an adaptive noise canceller is built from a Walsh filter with a new adaptive algorithm. The Walsh filter consists of a Walsh function. Since the Walsh functions are either even or odd functions, the covariance matrix in the tap gain adjustment algorithm can be reduced to a simple form. In this paper, minimization of the mean squre error is accomplished by a proposed adaptive algorithm. The conventional adaptation techniques use a fixed time constant convergence factor by trial and error methods. In this paper, a convergence factor is obtained that is tailored for each adaptive filter coefficient and is updated at each block iteration.

• Smart Structures and Systems
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• 제21권2호
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• pp.187-194
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• 2018

This paper focuses on the $H_{\infty}$ filter design problem for offshore steel jacket platforms. Its objective is to design a full-order state observer for offshore platforms in presence of unknown disturbances. To make the method more practical, it is assumed that the measured variables are available at discrete-time instants with time-varying sampling time intervals. By modelling the sampling intervals as a bounded time-varying delay, the estimation error system is expressed as a time-delay system. As a result, the addressed problem can be transformed to the problem of stability of dynamic error between the system and the state estimator. Then, based on the Lyapunov-Krasovskii Functional (LKF), a stability criterion is obtained in the form of Linear Matrix Inequalities (LMIs). According to the stability criterion, a sufficient condition on designing the state estimator gain is obtained. In the end, the proposed method is applied to an offshore platform to show its effectiveness.

• 한국물환경학회지
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• 제25권2호
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• pp.205-211
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• 2009

In this study, the membrane filter method was compared to the MPN method for the analysis of total coliforms from raw water using raw test waters and controls including 6 standard strains of coliforms, and the various factors were analyzed on the detection of general and fecal origin coliforms. The range of error rate for the detection of 5 standard strains using the membrane filter and the MPN methods was 0 to 6% and 45 to 133%, respectively. The error rate of the membrane filter method was lower than that of the MPN method. The membrane filter method (m-Endo) showed 10% (11 out of 111) of difference for the detection sensitivity of coliforms isolated from raw water compared to the MPN method (BGLB). The membrane filter method was less affected by the factors including temperature, turbidity, charcoals of powder form, contamination, and reverse pressure. In conclusion, the membrane filter method is a better method for the analysis of total coliforms from raw water than the MPN method, considering the accuracy of detection and the tolerance to various experimental factors.

• 한국통신학회논문지
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• 제33권4C호
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• pp.312-320
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• 2008

H.264/AVC에서 부호화 효율 개선을 위해 매크로 블록 기반 적응 보간 방법이 고려되어졌다. 이 방법에서 필터 선택 기준은 비트율과 왜곡 항들이 고려하여 좋은 성능을 발휘하지만 아직 개선의 여지를 남겨두고 있다. 따라서 본 논문에서는 기존 방법보다 높은 부호화 효율 개선을 위해 움직임 벡터와 예측 에러에 대한 두 가지 비트율과 복원 에러를 고려하여 새로운 필터 선택 기준을 제안한다. 부가적으로 선택된 필터 정보 전송을 위한 오버헤더 (overhead)를 줄이는 알고리듬을 나타낸다. 실험 결과는 제안 방법이 기존 방법에 비하여 우수한 성능을 보이고 H.264/AVC에 비해 전체 비트율이 평균 5.19% (참조 프레임: 1개)와 5.14% (참조 프레임: 5개) 절감된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

• 한국해양공학회지
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• 제17권6호
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• pp.83-90
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• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), and a Doppler velocity log (DVL), accompanied by a magnetic compass. The errors of inertial measurement units increase with time, due to the bias errors of gyros and accelerometers. A navigational system model is derived, to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 20. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors, and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o,f equations of motion of SAUV, using a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance, by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass, and a depth sensor. The error of the estimated position still slowly drifts in the horizontal plane, about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 춘계학술대회 논문집
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• pp.121-121
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• 2014

본 연구에서는 반도체 제조의 Diffusion 공정설비의 FFU (Fan Filter Unit) 진동에 의해 발생한 wafer 불량 현상을 규명 및 개선하였다. EFEM(Equipment Front End Module)의 Loading 부에 장착된 FOUP(Front Opening Unified Pod)에 들어 있는 Wafer 들이 설비 EFEM 하부로 떨어져 깨지거나 FOUP 내에서 겹침 현상이 발생하는 것을 확인하였다. 이에 생산현장의 모든 Diffusion 공정 설비를 조사하였으며, 그 결과 A 사(社)의 특정 설비에서만 발생되는 현상임을 확인하였다. 해당 A사(社)설비군에서만 월 평균 10 건의 Slot Mapping Error 가 발생하였으며, 이로 인해 Wafer가 재 제조된 매수가 월 평균 53 매로 확인되었다. 따라서 본 연구는 A 사(社)설비에서 발생하는 Mapping Error 의 원인 규명 및 개선을 위해 추진되었다. 총 12 개의 항목을 불량 발생 원인 후보 군으로 선정 후 예비 진단한 결과 FFU(Fan Filter Unit)에 의한 문제 발생 가능성이 가장 높을 것으로 추정되었다. 이에 따라 4 개의 서로 다른 물리적 환경/조건에서 진동을 측정하였으며, 최종 평가 결과 Motor 와 Blade 의 불균형에서 기인한 진동이 설비의 loader 부에 직접적으로 영향을 주는 것을 확인하였다. 진동 문제를 해결하기 위해 고 RPM blade 에서 저 RPM 및 유량 감소를 보완할 수 있는 신규모델로 교체하였다. 신규 Module(blade/motor) 장착 후 Load port 에서의 진동 측정 결과 개선 전 대비 91% 감소하였으며, 결과적으로 Slot mapping error 발생 건수가 50% 이상 감소되는 효과와 Wafer 재 제조 매수도 월 평균 약 43% 감소하는 효과를 얻을 수 있었다.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• 한국측량학회지
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• 제33권6호
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• pp.569-577
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• 2015

The navigation algorithm developed based on the extended Kalman filter (EKF) sometimes diverges when the linearity between the measurements and the states is not preserved. In this study, new update conditions together with two conditions from previous study for gravity gradient referenced navigation (GGRN) were deduced for the filter performance. Also, the effect of each update conditions was evaluated imposing the various magnitudes of the database (DB) and the sensor errors. In case the DB and the sensor errors were supposed to 0.1 Eo and 0.01 Eo, the navigation performance was improved in the eight trajectories by using part of gravity gradient components that independently estimate states located within trust boundary. When applying only the components showing larger variation, around 200% of improvement was found. Even the DB and sensor error were supposed to 3 Eo, six update conditions improved performance in at least seven trajectories. More than five trajectories generated better results with 5 Eo error of the DB and the sensor. Especially, two update conditions successfully control divergence, and bounded the navigation error to the 1/10 level. However, these update conditions could not be generalized for all trajectories so that it is recommended to apply update conditions at the stage of planning, or as an index of precision of GGRN when combine with various types of geophysical data and algorithm.

• 제어로봇시스템학회논문지
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• 제21권9호
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• pp.807-810
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• 2015

In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.