• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.826-829
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• 2004

Structural Dynamics Modification is very effective technique to improve structure's dynamic characteristics by adding or removing auxiliary structures, changing material property, changing shape of structure. In this research, using the surface grooving technique, shape of base structure was changed to improve its first natural frequency. Utilizing the result of frequency variation analysis, groove shape was formed gathering the many small embossing elements. For this process, Criterion Factor was introduced. To reduce its amount of calculation, the range of target area was restricted to their neighboring area and initial grooving point was selected using high-strain energy. This surface grooving technique was successfully applied to the HDD cover model.

• Journal of the Optical Society of Korea
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• v.7 no.2
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• pp.64-66
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• 2003

The optical gain and noise figure improved double-pass two-stage EDFA using a mirror, circulator, and gain-flattening filters is proposed. By double passing the pump light and removing the ASE propagating into the input part, the signal gain of 5 ㏈ and noise figure of 2.1 ㏈ are improved compared to the conventional single- and double-pass EDFA With gain-fattening filters in the second stage of EDFA, we obtain an improved flat gain with a gain flatness less than 1 ㏈ over 33-nm wavelength range at the 980-nm pump power of 86 ㎽.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.524-527
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• 2005

A society has progressed rapidly toward the highly advanced digital information age. However, noise is generated by several causes, when signal is processed. Therefore, methods for eliminating those noises have researched. There were the existing FFT(fast fourier transform) and STFT(short time fourier transform) for removing noise but it's impossible to know information about time and time-frequency localization capabilities have conflictive relationship. Therefore, for overcoming these limits, wavelet-based denoising methods that are capable of multiresolution analysis are applied to the signal processing field. However, existing threshold- and correlation-based denoising methods consider only statistical characteristics for noise, accordingly a lot of noise is acceptable as an edge and are impossible to remove AWGN and impulse noise, at the same time. Hence, in this paper we proposed wavelet-based new denoising algorithm and compared existing methods with it.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1320-1326
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• 2018

Digital video equipment is important in the 4th industrial revolution and is widely used in different fields for various purpose. Data of digital video equipment is exposed to noise due to different reasons including user environment and processing and such noise affect output and processing method. This can even cause error, resulting in decreased reliability of the equipment. In this research, it offers algorithm to effectively recover video by removing noise and impulse noise occurring during the process of channel delivery. This proposed algorithm recovers video by exploring valid pixel using directional local mask and noise determination. Then, valid pixel calculated goes through the final output calculation through comparative analysis on estimation. For comparing suggested method and algorithm, simulation is carried out. For checking the function of it, PSNR and profile are analyzed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2717-2723
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• 2015

Recently, digital image processing is being applied in various areas of broadcasting, communication, computer graphic and medical science. But, degradation of images occurs in the process of digital image acquisition, processing and transmission. Therefore, in order to remove the mixed noise, this paper suggested the image restoration algorithm to process salt and pepper noise with weighted filters according to 4 direction pixel changes after judging the noise and to process AWGN with weighted filters which have individually different characteristics. Regarding the processed results by applying Boat images which were corrupted by salt and pepper noise(P=40%), suggested algorithm showed the improvement by 1.33[dB], 1.41[dB], 0.51[dB] respectively compared with the existing CWMF, AWMF, MMF.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.175-181
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• 2011

We propose a novel algorithm for measuring the radius of tubes. This proposed algorithm is capable of effectively removing added noise and measuring the radius of tubes within allowable precision. The noise is removed by using a candidate true center that minimizes the standard deviation with respect to the radius. Further, the disconnection in data points resulting from noise removal is solved by using a connection algorithm. The final step of the process is repeated until the value of the standard deviation decreases to a small predefined value. Experiments were performed using circle geometries with added noise and a real tube with complex noise and that is used in the braking units of automobiles. It was concluded that the measurement carried out using the algorithm was accurate within 1.4%, even with 15% added noise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.41-45
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• 2019

In this paper, we propose the interference cancellation scheme of end-to-end method algorithm for power line communication (PLC) systems in smart grid. The proposed scheme estimates the channel noise information of receiver by applying a deep learning model at the receiver. Then, the estimated channel noise is updated in database. In the modulator, the channel noise which reduces the power line communication performance is effectively removed through interference cancellation technique. As an impulsive noise model, Middleton Class A interference model was employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the theoretical model based on additive white Gaussian noise. As a result, the proposed interference cancellation with deep learning improves the signal quality of PLC systems by effectively removing the channel noise. The results of the paper can be applied to PLC for smart grid and general communication systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.645-651
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• 2021

With the advent of the Fourth Industrial Revolution, modern society uses a diverse pool of devices. In this context, there is increasing interest in removing various kinds of noise arising in data transmission. However, it is difficult to restore image that damaged by mixed noise, and a digital filter that effectively restores an image according to the characteristics of the noise is required. In this paper, we propose a digital switching filter algorithm to remove mixed noise generated during digital image transmission. The proposed algorithm switches the filtering process through noise judgment and reconstructs the image using fuzzy weights and combined weights based on the pixel values inside the mask. To evaluate the proposed algorithm, we compared it with existing filter algorithms through simulation. Filtering results were expanded and compared for visual evaluation, and PSNR comparison was used for quantitative evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1483-1489
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• 2022

Recently, due to the influence of the 4th industrial revolution and the development of communication media, various digital video equipment are being used in industrial fields. Image data is easily damaged by noise in the process of acquiring and transmitting and receiving from the camera and sensor, and since the damaged image has a great effect on the processing of the system, noise removal is essential. In this paper, a weight filter algorithm using a weight graph is proposed to restoration images damaged by high-density impulse noise. The proposed algorithm obtains a weight graph using pixel values inside the filtering mask of the image, and restores the image by applying the final weight to the filtering mask. Simulation was conducted to analyze the noise removal performance of the proposed algorithm, and the magnified image and PSNR were used to compare with the existing method. The resulting image of the proposed algorithm showed excellent performance by removing high-density impulse noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.763-770
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• 2002

Recognition of CW Morse signals can be divided into several phases such as detection of tones and spaces, signal processing for removing noise from detected signals, decision of tones/spaces, mapping a sequence of tones and spaces into characters, error correction of a character message with textual repetition. In this paper, in order to cope with signal fading effectively we propose a signal detection method of identifying peaks in the frequency domain and present techniques for combining multiple frequency peaks and for removing residual signal components and noise. LMS adaptive method is applied for decision of tones/spaces, and initial value setting and malfunctioning conditions are analyzed. In recognition experiments, we used CW Morse signals collected by radio receivers and found that the proposed method achieves good recognition performance even in severe fading conditions.