• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.964-968
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• 2003

Hermetic rotary compressor is one of the most Important components for air conditioning system since it has a great effect on both the performance and the noise and vibration of He system. Noise and vibration of rotary compressor is occurred due to gas pulsation during compression process and unbalanced dynamic force. In order to reduce noise and vibration. it is necessary to identify sources of noise and vibration and effectively control then. Many approaches have been tried to identify noise sources of compressor. However, compressor noise source identification has proven to be difficult since the characteristics of compressor noise are complicated due to the interaction of the compressor parts and gas pulsation. In this work, Statistical Energy Analysis has been used to trace the energy flow in the compressor and identify transmission paths from the noise source to the sound field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.678-681
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• 2020

In this paper, we analyzed the noise figure of cascode low noise amplifier (LNA) based on the measured data of 65nm CMOS devices. By using the channel thermal noise model of transistors, we expanded noise figure equation and divided the equation into three parts to see its contributions to noise figure. We also varied design parameters such as bias point, transistor gate width, and operating frequency. Our results show that different noise sources dominate at the different operating frequencies. One can easily find the noise transition frequency with device models in ahead of the practical design. Therefore, this research provides a low noise design approach for different operating frequencies.

• 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.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.308-318
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• 2022

Noise is a serious issue. While sending images via electronic communication, Impulse noise, which is created by unsteady voltage, is one of the most common noises in digital communication. During the acquisition process, pictures were collected. It is possible to obtain accurate diagnosis images by removing these noises without affecting the edges and tiny features. The New Average High Noise Density Median Filter. (HNDMF) was proposed in this paper, and it operates in two steps for each pixel. Filter can decide whether the test pixels is degraded by SPN. In the first stage, a detector identifies corrupted pixels, in the second stage, an algorithm replaced by noise free processed pixel, the New average suggested Filter produced for this window. The paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. In this paper the comparison of known image denoising is discussed and a new decision based weighted median filter used to remove impulse noise. Using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structure Similarity Index Method (SSIM) metrics, the paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. A detailed simulation process is performed to ensure the betterment of the presented model on the Mini-MIAS dataset. The obtained experimental values stated that the HNDMF model has reached to a better performance with the maximum picture quality. images affected by various amounts of pretend salt and paper noise, as well as speckle noise, are calculated and provided as experimental results. According to quality metrics, the HNDMF Method produces a superior result than the existing filter method. Accurately detect and replace salt and pepper noise pixel values with mean and median value in images. The proposed method is to improve the median filter with a significant change.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.878-879
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.640-641
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• 2014

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.600-601
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• 2011

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.835-836
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• 2014

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.837-838
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• 2014

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.333-335
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• 2011

In the transmitting process of image processing system, images always be corrupted by impulse noise, especially random-valued impulse noise. So removing the random-valued impulse noise is very important, but it is also one of the most difficult case in image processing. The most famous method is the standard median filter, but at edge, the filter has a special feature which has a tendency to decrease the preserve. As a result, we proposed a filter that detection random-valued impulse noise firstly, next to use efficient method to remove the noise and preserve the details. And through the simulation, we compared with the algorithms and indicated that proposed method significant improvement over many other existing algorithms.