• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.12
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• pp.91-99
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• 2010

HVDC converter station consists of a number of equipment such as converter transformer, ac filter, thyristor valve and so on. They can be acoustic noise sources. In this paper, we analyzed the simulation results of the outdoor acoustic noise for HVDC converter station. It shows that maximum noise level in boundary of HVDC converter station exceeds regulation value. The main factors in generating maximum noise level are ac filter and converter transformer. Then we applied some soundproof countermeasures in HVDC converter station. Shielding wall is enough to reduce transformer noise level but not enough to reduce ac filter noise level. In case of ac filter, soundproof building is effective in satisfying noise level regulation in boundary of HVDC converter station. In addition, we also studied effects of season, soundproof woods, ground.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.6
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• pp.78-89
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• 2015

Conventional EMI filters have tried to use an active EMI filter as a series by the series connection of two EMI filters for CM and DM noise. However, the proposed filter is formed into one circuit by using the active EMI filter which is able to filter CM and DM noise components together. As a result, the active EMI filter showed the outstanding quality in mass and volume under 50% and electric characteristics have been compared to the passive EMI filter in approximately 150kHz~10MHz. Furthermore, the proposed circuit has simple circuit components by comparing with the series EMI filters, and electrical characteristics are similar. The noise have been attenuated to maximum 20dBuV.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.467-468
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• 1998

Impulsive noise appears as black and/or white spots in an image. It is usually caused by errors during the image acquisition or transmission through communication channels. This paper presents a study on the impulsive noise reduction filter of digital image. A much more effective method for removing impulse noise is weighted median filtering. But it loses some information by changing center value with no condition. We propose some new technique to change center value with some conditions. In this paper, the performance of conditional weighted median filter is compared to the commonly used median filter, mean filter, max/min filter, and weighted median filter. A quantitative comparison is performed on MSE (Mean Square Error), RMSE (Root Mean Square Error), and SNR (Signal to Noise Ratio). Proposed conditional weighted median filter can yield better performance than regular filters.

• Structural Engineering and Mechanics
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• v.47 no.3
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• pp.361-381
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• 2013

A Bayesian probabilistic method is proposed for online estimation of the process noise and measurement noise parameters for Kalman filter. Kalman filter is a well-known recursive algorithm for state estimation of dynamical systems. In this algorithm, it is required to prescribe the covariance matrices of the process noise and measurement noise. However, inappropriate choice of these covariance matrices substantially deteriorates the performance of the Kalman filter. In this paper, a probabilistic method is proposed for online estimation of the noise parameters which govern the noise covariance matrices. The proposed Bayesian method not only estimates the optimal noise parameters but also quantifies the associated estimation uncertainty in an online manner. By utilizing the estimated noise parameters, reliable state estimation can be accomplished. Moreover, the proposed method does not assume any stationarity condition of the process noise and/or measurement noise. By removing the stationarity constraint, the proposed method enhances the applicability of the state estimation algorithm for nonstationary circumstances generally encountered in practice. To illustrate the efficacy and efficiency of the proposed method, examples using a fifty-story building with different stationarity scenarios of the process noise and measurement noise are presented.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.591-596
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• 2011

Image denoising is a key issue in all image processing researches. Generally, the quality of an image could be corrupted by a lot of noise due to the undesired conditions of image acquisition phase or during the transmission. Many approaches to image restoration are aimed at removing either Gaussian or impulse noise. Nevertheless, it is possible to find them operating on the same image, which is called mixed noise and it produces a hard damage. In this paper, we proposed noise type classification method and a mixed nonlinear filter for mixed noise suppression. The proposed filtering scheme applies a modified adaptive switching median filter to impulse noise suppression and an efficient nonlinear filer was carried out to remove Gaussian noise. The simulation results based on Matlab show that the proposed method can remove mixed Gaussian and impulse noise efficiently and it can preserve the integrity of edge and keep the detailed information.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.25-35
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• 2022

The SAP(salt-and-pepper) noise changes the pixel value to the maximum and minimum values of the dynamic region of the pixel. For this reason, unlike white Gaussian noise, SAP noise can predict the ratio of noise relatively easily. Because the condition of the neighboring pixels that can be referenced changes according to the noise ratio, it is necessary to apply different noise reduction methods according to the noise ratio. This paper proposes an adaptive switching filtering algorithm which can eliminates the SAP noise. It consists of two phases. It first detects the location of the SAP noise and calculates the noise ratio. After that, the image is reconstructed using different methods depending on which of the three sections the calculated noise ratio belongs to. As a result of the experiment, the proposed method showed superior objective and subjective image quality compared to the previous methods such as MF, AFSWMF, NAMF and RWMF.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.871-886
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• 2011

This paper proposes a powerful SVM-ASM filter, the adaptive switching median(ASM) filter based on support vector machines(SVMs), to effectively reduce impulse noise in corrupted images while preserving image details and features. The proposed SVM-ASM filter is composed of two stages: SVM impulse detection and ASM filtering. SVM impulse detection determines whether the pixels are corrupted by noise or not according to an optimal discrimination function. ASM filtering implements the image filtering with a variable window size to effectively remove the noisy pixels determined by the SVM impulse detection. Experimental results show that the SVM-ASM filter performs significantly better than many other existing filters for denoising impulse noise even in highly corrupted images with regard to noise suppression and detail preservation. The SVM-ASM filter is also extremely robust with respect to various test images and various percentages of image noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.114-117
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• 2006

The air filter in engine intake system has a function of filtrating the dirt in the scavenging air as well as attenuating the noise. The noise attenuation within the air cleaner filter, however, has been regarded as negligible by the field engineers. In this paper, for the analysis of the acoustical performance of air filter, an acoustical model was suggested and the characteristics of air filter system were investigated. Fibrous structure of the filter element was modeled as a micro-perforated panel using the flow resistivity and porosity. The pleated geometry of the filter element was modeled as two coupled ducts that have permeable walls, in which each duct area was assumed being constant. Using such simplified geometry, a mathematical model was developed for the sound propagation within a narrow duct system. Visco-thermal effect was considered in modeling the sound propagation through such tubes; the filter box was modeled as a rigid rectangular box. By combining two models, a four-pole transfer matrix was derived. For the validation purpose, transmission loss was measured for a plastic rectangular box containing an air filter. A noticeable effect of the air filter element was observed by including the filter into the box. Comparing the predicted and measured data, we found that the predicted TL agrees well with experimental results, in particular, in magnitude and frequency at TL troughs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.409-411
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• 2016

Salt and pepper noise is caused by various causes such as camera malfunction, storage media memory error, and transmission channel error. Representative filters to remove salt and pepper noise include SMF(standard median filter), CWMF(center weighted median filter), and AMF(adaptive median filter). However previous filters have inadequate noise removal characteristics in high density salt-and-pepper noise environment. Therefore the study suggested a composite filter which, through noise evaluation, preserves original pixels when the central pixel is non-noise, and uses spatial weighted value mask and median when there is noise.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.83-88
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• 1989

This paper is a study on the design of adptive filter for QRS complex detection. We propose a simple adaptive algorithm to increase capability of noise cancelation in QRS complex detection with two stage adaptive filter. At the first stage, background noise is removed and at the next stage, only spectrum of QRS complex components is passed. Two adaptive filters can afford to keep track of the changes of both noise and QRS complex. Each adaptive filter consists of prediction error filter and FIR filter The impulse response of FIR filter uses coefficients of prediction error filter. The detection rates for 105 and 108 of MIT/BIH data base were 99.3% and 97.4% respectively.