• Journal of KSNVE
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• v.10 no.4
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• pp.642-647
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• 2000

Conventional cepstrum has been widely used to detect echo and fault signals embedded in noise. One of the problems of finding impulse signals using the conventional cepstrum in that it is normally very sensitive to signal to noise ratio (SNR). This paper proposes a signal processing method to detect impulse signal in noisy environment. Because the proposed method minimizes the variance of signal power at a cepstrum domain, it is suggested to be called as minimum variance cepstrum (MV cepstrum). Computer simulations have been performed to understand the characteristics of the MV cepstrum. Both mathematical approach and computer simulations confirmed that the MV cepstrum is a useful technique to detect impulse in noisy environment.

• ETRI Journal
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• v.35 no.4
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• pp.644-654
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• 2013

In this paper, a signal detection scheme for cognitive radio (CR) based on the Bussgang theorem is proposed. The proposed scheme calculates the statistical difference between Gaussian noise and the primary user signal by applying the Bussgang theorem to the received signal. Therefore, the proposed scheme overcomes the noise uncertainty and gives scalable complexity according to the zero-memory nonlinear function for a mobile device. We also present the theoretical analysis on the detection threshold and the detection performance in the additive white Gaussian noise channel. The proposed detection scheme is evaluated by computer simulations based on the IEEE 802.22 standard for the wireless regional area network. Our results show that the proposed scheme is robust to the noise uncertainty and works well in a very low signal-to-noise ratio.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.9-14
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• 2021

Recently, magnetic resonance imaging (MRI), which can acquire images with good contrast without exposure to radiation, has been widely used for diagnosis. However, noise that reduces the accuracy of diagnosis is essentially generated when acquiring the MR images, and by adjusting the parameters, the noise problem can be solved to obtain an image with excellent characteristics. Among the parameters, the number of excitation (NEX) can acquire images with excellent characteristics without additional degradation of image characteristics. In contrast, appropriate NEX setting is required since the scan time increases and motion artifacts may occur. Therefore, in this study, after fixing all MRI parameters through the MRiLab simulation program, we tried to evaluate the tendency of image characteristics according to changing NEX through quantitative evaluation of brain T2 weighted images acquired by adjusting only NEX. To evaluate the noise level and similarity of the acquired image, signal to noise ratio (SNR), contrast to noise ratio (CNR), root mean square error (RMSE) and peak signal to noise ratio (PSNR) were calculated. As a result, both noise level and similarity evaluation factors showed improved values as NEX increased, while the increasing width gradually decreased. In conclusion, we demonstrated that an appropriate NEX setting is important because an excessively large NEX does not affect image characteristics improvement and cause motion artifacts due to a long scan.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.665-670
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• 2016

This paper proposes a repeat-back jamming signal detection scheme using a correlation ratio test metric of a combined pseudo-random noise signal for global navigation satellite systems. The correlation ratio test metric allows for the monitoring of possible distortions in the signal correlation. The proposed scheme is a modified version of the correlation ratio test metric to detect a repeat-back jamming signal in a multipath environment. Through a Monte-Carlo simulation, it is confirmed that the proposed scheme detects almost the whole case, which is received a repeat-back jamming signal under the 6 dB jamming to signal power ratio.

• Journal of the Korea society of information convergence
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• v.6 no.2
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• pp.45-49
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• 2013

Electrocardiogram(ECG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of cadiac disease diagnosis with removing signal white-noise. Sampling signal was made with generating white-noise. The noise were removed using wavelet transforms and thresholding. Removed noise were compared numerical using SNR(signal to noise ratio). The results compared SNR showed that SURE method was 5.931, 4.9301 in 3, 5dB noise, uninversal was 3.6590, 1.9698 in 7, 9dB noise. De-noising by Thresholding removed noise effectively. ECG signal is expected to improve the accuracy of cadiac desease dianosis.

• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.105-114
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• 2016

In this study, For assessment of triangular fibrocartilage complex (TFCC) injury, we acquired images by fat suppressed 3D fast spoiled gradient recalled T1 and fat suppressed Isotropic 3D fast spin echo T1 techniques. For quantitative evaluation, measured signal to noise ratio and contrast to noise ratio and verified statistical significance between two imaging techniques by Mann-Whitney U verification. And for qualitative evaluation, marked 4-grade scoring (0: non diagnostic, 1: poor, 2: adequate, 3: good) on shape of TFCC, artifacts by partial volumes, description of the lesions by two radiologist, verified coincidence between 2 observer using Kappa-value verification. We used 3.0 Tesla MR equipment and 8-channel RF coil for imaging acquisition. As quantitative evaluation results, signal to noise ratio and contrast to noise ratio value of Isotropic 3D fast spin echo T1 technique is higher in every image sections, also between two imaging techniques by Mann-Whitney U verification was statistically significant (p < 0.05). As qualitative results, observer 1, 2 marked a higher grade on Isotropic 3D FSE T1 technique, coincidence verification of evaluation results between two observers by Kappa-value verification was statistically significant (p < 0.05). As a result, during MRI examination on TFCC injury, fat suppressed Isotropic 3D fast spin echo T1 technique is considered offering more useful information about abnormal lesion of TFCC.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.483-489
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• 2016

This paper proposes a repeat-back jamming signal detection scheme that utilizes a combined pseudo random noise signal that is effective for processing a global positioning system (GPS) repeat-back jamming signal with the early minus late phase scheme to alleviate any existing multipath signal detection. The proposed scheme uses the combined pseudo random noise signal to treat repeat-back jamming signals like similar multipath signals and can effectively detect a repeat-back jamming signal by applying the early minus late phase scheme to a combined pseudo random noise signal. Through a Monte-Carlo simulation, the detection probability of the proposed scheme is better than the one of the conventional scheme under low jamming to signal power ratio.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.1
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• pp.55-62
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• 1983

The error rate performance of phase shift Keyed(PSK) signal has been evaluated in terms of carrier-to-noise ratio(CNR), carrier-to-interferer ratio(CIR), impulsive index, and the phase difference between signal and interferer in the environment of cochannel PSK inter-ference and impulsive noise. We hays derived a general equation of the probability density function (p.d.f.) of output of coherent phase detector. And the error rate of the received binary PSK(BPSK) signal has been numerically evaluated. The graphic results show us that the best case is the situation of the signal and the inter- ferer meet with orthogonal phase.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2239-2246
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• 2011

In image signal processing, image signal is corrupted by various noises and caused the degradation phenomenon. And Images often corrupted by AWGN(additive white gaussian noise) and impulse noise which called mixed noise. In this paper, the algorithm is proposed to remove mixed noise while keeping edge information. The proposed algorithm first classifies the noise type, if the classify result is AWGN, then the mean of the output after using self-adaptive weighted mean filter and median value will be the outfiltering value. And if the noise type is impulse noise, then the noise is removed by a modified nonlinear filter. Also we compare existing methods through the simulation and using PSNR(peak signal to noise ratio) as the standard of judgement of improvement effect. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2798-2804
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• 2010

The audio and image signal are corrupted by various noises in signal processing, many studies are being accomplished to restore those signals. In this paper, the algorithm is proposed to remove additive Gaussian noise and impulse noise at one dimension signal like an speech signal. The algorithm is composed to remove Gaussian noise after removing impulse noise. And the method using wavelet coefficient accumulation is used to remove the Gaussian noise, and the median filter based on element deviation is applied to remove the impulse noise. Also we compare existing methods using SNR(signal-to-noise ratio) as the standard of judgement of improvemental effect.