• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.779-781
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• 2013

다양한 멀티미디어 서비스에 대한 요구가 증가됨에 따라, 영상을 정보전달의 수단으로 사용하기 위한 기술들이 급격히 발전하고 있다. 영상에 첨가되는 여러 가지 잡음을 제거하기 위해, 평균 필터, 메디안 필터, 가중치 필터 방법 등이 제안되었으나 기존의 방법들은 잡음제거 및 에지 보존 성능이 미흡하다. 따라서 본 논문에서는 영상에 첨가되는 복합잡음을 효과적으로 제거하기 위해 먼저 잡음을 판단한 후, 변형된 메디안 필터와 적응 가중치 평균 필터를 이용하여 처리하는 알고리즘을 제안하였다. 그리고 시뮬레이션을 통해 기존의 방법들과 비교하였으며 판단의 기준으로 PSNR(peak signal to noise ratio)을 사용하였다.

• International journal of advanced smart convergence
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• 제1권1호
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• pp.48-51
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• 2012

The conventional method for filtering force plate data, low-pass filtering, does not always give accurate results when applied to force data from a custom-made, instrumented treadmill. Therefore, this study compares low-pass filtered data to the same data passed through a wavelet filter. We collected data with the treadmill running. However these include motor noise with ground reaction force at two force plates. We found that he proposed wavelet method eliminated motor noise to result in more accurate force plate data than the conventional low-pass filter, particularly at high speed motor operation. In this study we suggested the convolution wavelet (CNW) which was compared to that of a low-pass filter. The CNW showed better performance as compared to band-pass filtering particularly for low signal-to-noise ratios, and a lower computational load.

• Journal of Power Electronics
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• 제16권3호
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• pp.1236-1243
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• 2016

This paper presents the analysis and design of an active electromagnetic interference (EMI) filter (AEF) for the common-mode (CM) noise reduction of switching power converters. The features of the several types of AEFs are discussed and compared in terms of implementation. The feed-forward AEF with a voltage-sensing and voltage-cancellation (VSVC) structure is implemented for an LLC resonant converter to replace a multiple-stage passive EMI filter and thereby reduce CM noise. The characteristics and performance of the VSVC-type AEF are investigated through theoretical and experimental works.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 하계학술대회 논문집
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• pp.369-371
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• 2007

Due to the measurement noise or system noise, the performance of photovoltaic power generation system can be degraded. If this noise is contained in the solar array voltage measurement signal, the correct operation of the maximum power point tracker can not be guaranteed. The application of the extended Kalman filter to the photovoltaic system can obtain enhanced states estimation result. The Kalman filter provides a recursive solution to optimally estimate from random noise signals. Additionally, as a consequence of Kalman filter, the unmeasurable state such as inductor current can be estimated without current sensor. The methods for system modeling and extended Kalman filter design are presented and the experimental results verify the validity of the proposed system.

• 디지털산업정보학회논문지
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• 제19권2호
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• pp.57-68
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• 2023

Because salt and pepper noise is a type of impulse, even a small amount of noise could cause a large image degradation. In this paper, we proposed a salt-and-pepper noise removal method using the convolutional neural network. It consists of four phases. In the first step, the proposed method reconstructs noisy image using a traditional salt-and-pepper noise reduction method, and in the second step, the result image of previous step is filtered with Gaussian low pass filter. After that, we reconstruct the filtered image using convolution neural network. In the last step, the pixels with salt-and-pepper noise are replaced with the result of previous phase. Simulation results show that the proposed method yields not only objective image qualities(PSNR, SSIM) but also subjective image qualities for all SAP noise ratios.

• 융합신호처리학회논문지
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• 제11권4호
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• pp.270-277
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• 2010

BAMS(Baysian Adaptive Multiresolution Smoother) 필터는 모의실험 없이 Bayes 추정에 기초한 웨이블릿 축소기법에 의해 잡음을 제거하며 따라서 실시간 처리가 가능하다. BAMS 필터에 의한 영상잡음 제거 성능은 웨이블릿 분해 각 대역의 잡음분산에 크게 의존한다. 기존의 BAMS 필터는 웨이블릿 분해의 고주파 대역에서 사분위 통계량을 이용하여 잡음분산을 추정하여 잡음을 제거하였다. 본 논문에서는 영상신호의 중간대역을 포함한 잡음제거를 위해 변형된 사분위 통계량 및 모노토닉 변환으로 중간대역 잡음편차 추정하고 이를 이용해서 중간대역 및 고주파 대역의 영상잡음을 제거한 결과 중간대역의 잡음을 제거하므로 약 2[dB]정도의 PSNR이 증가하였으며 잡음편차가 작은 영상의 잡음제거에서도 효과가 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3242-3265
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• 2023

Ensuring reliability of a machinery system involve the prediction of remaining useful life (RUL). In most RUL prediction approaches, noise is always considered for removal. Nevertheless, noise could be properly utilized to enhance the prediction capabilities. In this paper, we proposed a novel RUL prediction approach based on noise injection and a Kalman filter ensemble of modified bagging predictors. Firstly, we proposed a new method to insert Gaussian noises into both observation and feature spaces of an original training dataset, named GN-DAFC. Secondly, we developed a modified bagging method based on Kalman filter averaging, named KBAG. Then, we developed a new ensemble method which is a Kalman filter ensemble of KBAGs, named DKBAG. Finally, we proposed a novel RUL prediction approach GN-DAFC-DKBAG in which the optimal noise-injected training dataset was determined by a GN-DAFC-based searching strategy and then inputted to a DKBAG model. Our approach is validated on the NASA C-MAPSS dataset of aero-engines. Experimental results show that our approach achieves significantly better performance than a traditional Kalman filter ensemble of single learning models (KESLM) and the original DKBAG approaches. We also found that the optimal noise-injected data could improve the prediction performance of both KESLM and DKBAG. We further compare our approach with two advanced ensemble approaches, and the results indicate that the former also has better performance than the latters. Thus, our approach of combining optimal noise injection and DKBAG provides an effective solution for RUL estimation of machinery systems.

• 대한전자공학회논문지SP
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• 제46권3호
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• pp.44-51
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• 2009

본 논문에서는 상관에 기반 한 비선형 합성필터를 이용한 왜곡과 잡음에 강인한 얼굴인식 방법을 연구한다. 상관도 기반 방법은 얼굴 영역의 검출과 인증을 동시에 수행하여 보다 신속한 처리를 할 수 있다는 장점이 있다. 최적화된 비선형 합성필터는 학습영상의 출력 값을 일정하게 유지하면서 입력 영상과 잡음의 필터 출력에너지를 최소화함으로써 얻어진다. 입력 영상의 출력에너지를 최소화하여 허위표적과의 식별력을 부여하고 잡음의 출력에너지를 최소화하여 가산성 잡음에 대한 강인성을 증대한다. 본 논문에서는 비선형 합성필터를 두 개의 학습 영상으로 구성하여 표적의 왜곡과 저해상도 그리고 잡음 환경 하에서 얼굴 인증을 실험하였다. 실험결과는 비선형 합성필터가 SDF(synthetic discriminant function) 필터와 비교하여 ROC(receiver operating characteristics) 커브에서 우수한 성능을 보인다.

• 대한의용생체공학회:의공학회지
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• 제23권5호
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• pp.333-340
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• 2002

생체신호 수집시 전력선 잡음은 일반적인 잡음원이다. 증가평가필터(Incremental Estimation Filter. IEF)는 생체신호, 특히, 심전도 (Electrocadiogram, ECG) 신호에 있어서 전력선 잡음을 제거하기 위해 사용되어 왔다. 증가평가필터의 잡음제거 성능에 영향을 미치는 상수 값의 증가인자는 입력신호에 따라서 경험적으로 혹은 실험적으로 결정되고 있다. 본 논문에서는 증가인자의 시변(time-varying) 제어를 위해 신경망을 이용한 증가평가필터 설계를 제시하고 있다. 제안된 증가평가필터는 인위적인 신호뿐만 아니라 MIT/BIH 데이터베이스의 실제 심전도 신호에 적용함으로써 평가하였으며, 잡음제거 성능의 상대적인 비교를 위해 적응잡음제거기와 기존의 증가평가필터등과 비교하였다. 실험결과 신경망에 근거한 증가평가필터는 수렴속도와 특정 주파수에서의 잡음제거에서 기존의 적응필터보다 우수함을 보여주었다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.780-783
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• 2004

Recently Intake noise has been extensively studied to reduce the engine noise. In order to diminish intake noise several resonators were added to the intake system. However this can cause a reduction of engine output power and an increase of fuel consumption. In this study, active noise control simulation of the Filtered-x LMS algorithm is applied real instrumentation intake noise data under rapid acceleration because intake noise is more excessively increased under the such a harsh condition. But the FXLMS algorithm has poor control performance when the system is disturbed. Thus modified FXLMS algorithm using L-point running average filter is developed to improve the control performance under the rapid acceleration and disturbance. The noise reduction quantity of modified Filtered-x LMS algorithm is more than original one in two cases. In the case of control for real instrumentation intake noise data, maximum residual noise of modified FXLMS algorithm is 2.5 times less than applied the FXLMS and also in the case of disturbed, the modified FXLMS algorithm shows excellent control performance but FXLMS algorithm cat not control.