• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.399-402
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• 2000

In this paper, we present a regularized mixed norm multichannel image restoration algorithm. The problem of multichannel restoration using both within- and between- channel deterministic information is considered. For each channel a functional which combines the least mean squares (LMS), the least mean fourth(LMF), and a smoothing functional is proposed, We introduce a mixed norm parameter that controls the relative contribution between the LMS and the LMF, and a regularization parameter that defines the degree of smoothness of the solution, both updated at each iteration according to the noise characteristics of each channel. The novelty of the proposed algorithm is that no knowledge of the noise distribution for each channel is required, and the parameters mentioned above are adjusted based on the partially restored image.

• 제어로봇시스템학회논문지
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• 제20권8호
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• pp.849-853
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• 2014

In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.

• 전자공학회논문지B
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• 제32B권7호
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• pp.974-988
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• 1995

In this paper, we propose a range image segmentation algorithm using robust regression. We derive a least $\kappa$th-order square (LKS) method by generalizing the least median of squares (LMedS) method and compare it with the conventional robust regressions. The LKS is robuster against outliers than the LMedS and shows performance similar to the residual consensus (RESC). The RESC uses the predetermined number of sorted residuals, whereas the LKS uses an adaptive parameter determined by given observations rather than the a priori knowledge. Computer simulation with synthetic and real range images shows that the proposed LKS algorithm gives better performance than the conventional ones.

• 한국통신학회논문지
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• 제25권5B호
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• pp.830-841
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• 2000

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at iteration a upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RL algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the (B+1)times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• 대한의용생체공학회:의공학회지
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• 제41권1호
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• pp.28-34
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• 2020

In this paper, we introduce motion artifact reduction algorithm for interleaved MRI using an advanced 3D approximation algorithm. The motion artifact framework of this paper is data corrected by post-processing with a new 3-D approximation algorithm which uses data structure for each voxel. In this study, we simulate and evaluate our algorithm using Shepp-Logan phantom and T1-MRI template for both scattered dataset and uniform dataset. We generated motion artifact using random generated motion parameters for the interleaved MRI. In simulation, we use image coregistration by SPM12 (https://www.fil.ion.ucl.ac.uk/spm/) to estimate the motion parameters. The motion artifact correction is done with using full dataset with estimated motion parameters, as well as use only one half of the full data which is the case when the half volume is corrupted by severe movement. We evaluate using numerical metrics and visualize error images.

• 한국음향학회지
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• 제16권3호
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• pp.38-44
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• 1997

본 연구에서는 Bussgang 계열의 복소수형 LMF-Sato 및 LMSF-Sato 블라인드 등화 알고리즘을 유도한 후, 이들 알고리즘에 대한 수렴속도, 정상상태에서의 수렴특성 및 안정성을 기종의 LMS-Sato 및 LMSF-Sato 알고리즘이 LMS-Sato 알고리즘에 비해 더 나은 수렴 특성을 보여 주었다. 그러나 계수벡터의 초기 추정오차가 큰 경우 LMF-Sato 알고리즘에 비해 더 나은 수렴 특성을 보여 주었다. 그러나 계수벡터의 초기 추저오차가 큰 경우 LMF-Sato 알고리즘은 안정성이 떨어지는 특성을 보여준 반면, LMSF-Sato 알고리즘은 좋은 수렴 특성과 견실성을 고루 갖추고 있음을 보여 주었다.

• 대한의용생체공학회:의공학회지
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• 제28권5호
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• pp.665-675
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• 2007

The morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart. Generally ST segment deviation is concerned with myocardial abnormality. The aim of this study is to detect the change of ST in shape using a polynomial approximation method and the reference ST type. The developed algorithm consists of feature point detection, ST level detection and ST shape classification. The detection of QRS complex is accomplished using it's the morphological characteristics such as the steep slope and high amplitude. The developed algorithm detects the ST level change, and then classifies the ST shape type using the polynomial approximation. The algorithm finds the least squares curve for the data between S wave and T wave in ECG. This curve is used for the classification of the ST shapes. ST type is classified by comparing the slopes of the specified points between the reference ST set and the least square curve. Through the result from the developed algorithm, we can know when the ST level change occurs and what the ST shape type is.

• 한국통신학회논문지
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• 제31권12A호
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• pp.1214-1222
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• 2006

본 논문에서는 orthogonal frequency-division multiple-access 스마트 안테나 시스템을 위한 효율적인 도래각 추정 기반의 적응 빔 형성 알고리즘을 제안한다. 제안된 알고리즘은 추정된 도래각 정보를 이용하여 원하는 신호의 방향으로 주 빔 (main beam)을 형성하는 반면, 간섭 신호의 방향에는 null을 형성함으로써 간섭 신호를 효율적으로 제거한다. 또한, 다중 경로 신호에 대한 빔 형성 출력들을 효율적으로 결합함으로써 공간 다이버시티 이득을 얻을 수 있다. 제안된 알고리즘의 효율성을 입증하기 위해 셀룰러 이동통신 환경에서 WiBro 시스템을 목표 시스템 (target system)으로 설정하여 알고리즘의 성능을 분석하고 least-sqaures 빔 형성 알고리즘과 성능을 비교한다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.384-387
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• 1998

This paper presents a newly developed speed sensorless drive using RLS(Recursive Least Squares) based on Neural Network Training Algorithm. The proposed algorithm based on the RLS has just the time-varying learning rate, while the well-known back-propagation (or generalized delta rule) algorithm based on gradient descent has a constant learning rate. The number of iterations required by the new algorithm to converge is less than that of the back-propagation algorithm. The RLS based on NN is used to adjust the motor speed so that the neural model output follows the desired trajectory. This mechanism forces the estimated speed to follow precisely the actual motor speed. In this paper, a flux estimation strategy using filter concept is discussed. The theoretical analysis and experimental results to verify the effectiveness of the proposed analysis and the proposed control strategy are described.

• 전기학회논문지
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• 제57권12호
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• pp.2139-2146
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• 2008

This paper presents a numerical algorithm for fault location estimation which used to data from both end of the transmission line. The proposed algorithm is also based on the synchronized voltage and current phasor measured from the PMUs(Phasor Measurement Units) in the time-domain. This paper has separated from two part of with/without shunt capacitance(short/long distance). Most fault was arc one-ground fault which is 75% over [1]. so most study focused with it. In this paper, the numerical algorithm has calculated to distance for ground fault and line-line fault. In this paper, the algorithm is given with/without shunt capacitance using II parameter line model, simple impedance model and estimated using DFT(Discrete Fourier Transform) and the LES(Least Error Squares Method). To verify the validity of the proposed algorithm, the EMTP(Electro- Magnetic Transient Program) and MATLAB did used.