• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.2
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• pp.33-38
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• 2008

The baseline wander of ECG makes difficult to detect P-, Q-, R- and S-wave. This paper presents and compares two method to remove the baseline wander of ECG using slope traceing waves. For the first method that had been proposed already[1], the ascending slope tracing method is used to eliminate baseline wander. And the second method employs the contour of the approximated S-wave to remove baseline wander. These two methods are common to use the slope tracing wave. However, the first one is to get difference signals between the ascending tracing waves and ECG signals, and the other is to remove baseline wander using the contour of the approximated S-wave obtained from descending slope waves. To evaluate these methods, we apply to MIT/BIH database.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.11
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• pp.9-15
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• 2004

We propose optimal interference rejection weight for multistage parallel nulling (MPN) partial parallel interference cancellation (PPIC) receiver previously proposed to enhance the performance of V-BLAST for downlink multiple-input multiple-output (MIMO) multicarrier (MC)-code division multiple access (CDMA) systems. MPN-PPIC method proposed in [1] was based on the parallel interference cancellation (PIC) with fixed interference rejection weight obtained experimentally. However, the fixed weight can not be adapted to various systems efficiently, thus we proposed method for the optimal interference rejection weight based on the received signal to interference and noise ratio (SINR), and the performance of the proposed method was evaluated through computer simulation comparing with the previous method. We obtained performance gains of 2.5 dB ~ 5 dB for BER of 10$^{-3}$ .

• Restorative Dentistry and Endodontics
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• v.30 no.3
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• pp.215-220
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• 2005

It is common for clinicians to encounter endodontically tl·treated teeth that contain posts within their roots. If endodontic treatment is failed, these posts must be removed to facilitate successful nonsurgical retreatment. There have been many techniques such as ultrasonic instrument, Ruddle post removal system, Eggler post remover and Masserann kit developed to facilitate removal of posts from the root canal space. But these methods may be disadvantageous because long length of time required for post removal and fracture of post or teeth. In now days new post removal technique using ATD automatic bridge remover was introduced. Advantages of this method are simple and short time consuming compare to others. This article served as a successful case report of post removal using ATD automatic bridge remover.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.165-173
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• 2014

This paper presents a fast and high-quality haze removal method by the modification of the conventional transmission estimation process. In the conventional haze removal method, the halo and blocking artifacts arises while estimating the transmission. In order to effectively reduce the artifacts, the proposed method employs the maximum filter after the calculation of the dark channel. Because of the reduction of the artifacts, the proposed method can simplify the transmission refinement process without sacrificing the quality of the results: this paper proposes to use the single-channel guided filter instead of the multi-channel guided filter. The experimental results demonstrate that the quality of the dehazed results by the proposed transmission correction process is improved and the haze removal speed is increased by up to 59.6%, when compared to the conventional ones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6C
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• pp.589-602
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• 2006

잡음은 음성과 관련된 시스템의 성능을 제한하는 주된 원인이기 때문에 음성향상과 관련된 연구는 꾸준히 계속되어왔다. 전통적인 음성향상 방법은 무성음과 잡음을 구분하지 알기 때문에 잡음제거 과정에서 무성음이 함께 제거되는 단점이 있으며, 웨이블릿 기반의 전통적인 잡음제거 방법은 각 대역마다 동일한 문턱값을 사용하기 때문에 시변 환경에서 성능이 떨어지는 단점이 있다. 이 단점들을 개선하기위해 다중대역 파워 차감법과 Perceptual 웨이블릿 패킷 분해를 이용한 웨이블릿 기반의 개선된 음성향상 방법을 제안한다. 전처리 과정으로 다중대역 파워 차감법을 사용하여 광대역 잡음을 제거하고 뮤지컬 잡음의 발생을 줄이며, psycho-acoustic 모델 기반 Perceptual 웨이블릿 패킷으로 신호를 분해한 후 각 웨이블릿 노드의 엔트로피 비율과 음성검출을 이용하여 무성음/유성음/잡음을 구분한다. 구분된 신호에 따라 각 웨이블릿 노드마다의 문턱값을 기준으로 웨이블릿 Shrinkage를 적용하여 잡음을 제거하고 무성음이나 파워가 작은 유성음이 제거되는 오류를 최소화한다. 또한 잡음 파워 추정 과정에 적응적으로 망각 계수를 선택하여 잡음 파워 추정 오류를 최소화한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.47-54
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• 2005

In general, wavelet coefficients are composed of a few large coefficients and a lot of small coefficients. In this paper, we propose image denoising algorithm using Bernoulli-Gaussian mixture model based on sparse characteristic of wavelet coefficient. The Bernoulli-Gaussian mixture is composed of the multiplication of Bernoulli random variable and Gaussian mixture random variable. The image denoising is performed by using Bayesian estimation. We present an effective denoising method through simplified parameter estimation for Bernoulli random variable using local expected squared error. Simulation results show our method outperforms the states-of-art denoising methods when using orthogonal wavelets.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.469-477
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• 2000

본 연구에서는 부도예측용 인공신경망 모형의 입력노드를 선정하기 위한 방법론으로 연결강도판별분석(Link Weight Discrimination Analysis)에 의한 약체뉴론제거법(Weak-Linked Neuron Elimination)과 강체뉴론선택법 (Strong-Linked Neurons Selection)을 제안한다. 연결강도판별분석이란 적절한 학습이 끝난 인공신경망 모형에서 입력노드와 연결되는 가중치의 합에 대한 절대값인 연결강도 판별식(Link Weight Discrimination)에 의해 해당 입력노 드가 출력노드에 미치는 영향정도를 분석하는 것이다. 한편 강체연결뉴론선택법은 선처리를 통해 얻어진 학습된 인공신경망의 입력노드 가운데서 연결강도판별식이 큰 뉴론만을 본처리의 입력노드로 선정하는 것인데 비해 약체연결뉴론제거법은 연결강도판별식이 일정 값 즉, 연결강도 판별임계치(Link Weight Discrimination Cut off Value) 보다 낮은 입력노드를 제외하고 나머지 입력노드만을 본처리의 입력노드로 선정하는 것이다. 본 연구에서는 강체연결뉴론선택법과 약체연결뉴론제거법을 각각 정형적인 방법론으로 정립하고 이 방법론에 의해 부도예측용 인공신경망을 구축하여 각각의 모형을 의사결정트리에 의해 선정된 인공신경망 모형 및 선처리 과정을 거치지 않은 인공신경망 모형과 성능을 비교, 분석하여 본 연구에서 제안한 방법론의 타당성을 제시하였다.

• Investigative Magnetic Resonance Imaging
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• v.8 no.1
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• pp.1-8
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• 2004

Purpose : Information about electrical activity inside the brain during fMRl scans is very useful in monitoring physiological function of the patient or locating the spatial position of the activated region in the brain. However, many additional noises appear in the EEG signal acquired during the MRI scan. Gradient induced noise is the biggest one among the noises. In this work, we propose a gradient noise reduction method using the independent component analysis (ICA) method. Materials and Methods : We used a 29-channel MR-compatible EEG measurement system and a 3.0 Tesla MRI system. We measured EEG signals on a subject lying inside the magnet during EPI scans. We selectively removed the gradient noise from the measured EEG signal using the ICA method. We compared the results with the ones obtained with conventional averaging method and PCA method. Results : All the noise reduction methods including the averaging and PCA methods were effective in removing the noise in some extent. However, the proposed ICA method was found to be superior to the other methods. Conclusion : Gradient noise in EEG signals acquired during fMRI scans can be effectively reduced by the ICA method. The noise-reduced EEG signal can be used in fMRI studies of epileptic patients or combinatory studies of fMRI and EEG.

• 전기의세계
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• v.34 no.2
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• pp.94-98
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• 1985

Autocorrelation에 관계되는 Fourier변환의 기본적인 성질을 이용하여 speckle잡음제거가 power spectrum estimation 문제와 같이 해석될 수 있다는 것을 보였고 spectral estimation 방법으로서 최대 entrppy방법을 사용하여 딴 방법들과 비교하여 볼때 좋은 결과를 얻었다. 앞으로 2차원 test object까지의 확장, 이 알고리즘의 각 파라메타들에 대한 sensitivity, optimal한 Hanning window크기 판단 기준으로서 normalized mean squared error(NMSE)를 사용하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.145-155
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• 2015

Noise reduction has been actively studied in the digital image processing and recently, block-based denoising algorithms are widely used. In particular, a low rank approximation employing WNNM(Weighted Nuclear Norm Minimization) and block-based approaches demonstrated the potential for effective noise reduction. However, the algorithm based on low rank a approximation generates the artifacts in the image restoration step. In this paper, we analyzes the image content using the STFT(Short Time Fourier Transform) and proposes an effective method of minimizing the artifacts generated from the conventional algorithm. To evaluate the performance of the proposed scheme, we use the test images containing a wide range of noise levels and compare the results with the state-of-art algorithms.