• 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.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1303-1311
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• 2008

In this paper, we analyzed the error rate performance of convolution coded 16 QAM signal in impulsive noise Environments. We used convolution code and selective combining diversity for performance improvement. We analyzed the error rate performance of 16 QAM signal in impulsive noise environments compared with gaussian noise environments. As a result of analysis, there is a BER segment where the efficiency of system does not improve until which limit to raise a signal power potential from impulsive noise environment. when the signal power potential which goes over this limit is supplied, BER efficiency improve much more.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.33-38
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• 2005

Degradation is generated by several causes in the process of digitalization or transmission of data. And its essential cause is noise. Therefore, researches for wavelet-based methods which reconstruct signal degraded by noise have continued. In AWGN(addtive white gaussian noise) environment, the general trend for denoising is to use the thresholding method. Reconstructed signal includes a lot of noise because these methods only consider statistical characteristic regarding noise. In this paper, we present a new method which uses the cumulation of wavelet detail coefficients. As a result, reconstruction of edges and denoising performance are improved. Also we compare existing methods using SNR(signal-to-noise ratio) as the standard of judgement of improvemental effect.

• Phonetics and Speech Sciences
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• v.3 no.4
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• pp.117-124
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• 2011

This study investigated the effects of the types of noise and signal to noise ratios (SNRs) on speech intelligibility of an adult with dysartrhia. Speech intelligibility was judged by 48 naive listeners using a word transcription task. Repeated measures design was used with the types of noise (multi-talker babble/environmental noise) and SNRs (0, +10 dB, +20 dB) as within-subject factors. The dependent measure was the percentage of correctly transcribed words. Results revealed that two main effects were statistically significant. Listeners performed significantly worse in the multi-talker babble condition than the environmental noise condition, and they performed significantly better at higher levels of SNRs. The current results suggested that the multi-talker babble and lower level of SNRs decreased the speech intelligibility of adults with dysarthria, and speech-language pathologists should consider environmental factors such as the types of noise and SNRs in evaluating speech intelligibility of adults with dysarthria.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.774-779
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• 2004

This paper addresses the way in which we can find where impact noise sources are. Specifically, we have an interest in the case that the signal is embedded in noise. We propose a signal processing method that can identify impulsive sources’location. The method is robust with respect to noise; spatially distributed noise. This has been achieved by a beamforming method with regard to cepstrum domain is used. It is noteworthy that the cepstrum has the ability to detect periodic pulse signal in noise. Numerical simulation and experiments are performed to verify the method. Results show that the proposed technique is quite powerful for localizing the faults in noisy environments. The method also required less microphones than conventional beamforming method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.961-968
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• 2007

Today, we can use radio communication device anywhere-anytime. Sometimes, we use the device in acoustic noise environment. The acoustic noise makes many problems in communication system. In acoustic noise environment, speaker cannot send clear information to receiver, because the received signal includes both speech signal and noise signal. A digital filter is useful to remove noise to get desired signal. One of methods is the adaptive digital filter using the adaptive noise canceller that automatically adjust filter parameters. This thesis addresses articulation algorithms against actual acoustic noises by means of two adaptive filtering methods. One is the adaptive noise canceller with two input channels and another is the spectral subtraction filter with one input channel. The experimental result from the proposed filter shows that the adaptive noise canceller is useful to reduce the non-stationary noises, while the spectral amplitude filter is effective for stationary noises.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.818-827
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• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.671-673
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• 2016

In image data, noise occurs due to various external factors in the process of obtaining and transmitting. There are various types of noise according to the cause and form and research to remove this noise is being continued. Therefore the study suggested a way to filter to restore images damaged by salt and pepper noise which preserves non-noise signal and processes noise signal by expanding mask size according to the local mask noise density. In addition, as an objective evaluation standard of improvements, the study used PSNR(peak signal to noise ratio) to compare with previous methods.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.84-89
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• 2002

In this paper, we present the design method of noise reduction circuit in telephonic system. The circuit consists of compressor, expander and a filter. The basic idea of a proposed method compresses the audible signal in order to mask the channel noise during transmission and then expand at the reverse rate the transmitted signal to naturally recover the original signal. Of course, there should be no distortion or other degradation of the audio itself in passing through companding(compress/expand) cycle. In the compressing process, the gain of compressor is automatically controlled by the envelope level of input signal in order to increase the effective dynamic range of input signal and to improve the signal to noise ratio. The compressed rate is the root time of a audible signal. The compressed signal should be expanded at the square time of the signal to recover a original signal. Simulation shows the proposed method improves the performance of the noise reduction of a channel noise as well as stability.