• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.59-67
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• 2006

OFDM (Orthogonal frequency Division Multiplexing) systems convert serial data stream to N parallel data streams and modulate them to N orthogonal subcarriers. Thus spectrum utilization efficiency of the OFDM systems are high and high-speed data transmission is possible. However, with the OFDM systems using the same modulation method at all subcarriers, the error probability is dominated by the subcarriers which experience deep fades. Therefore, in order to enhance the performance of the system adaptive modulation is required, with which the modulation methods of the subcarriers are determined according to the estimated SNRs. The IEEE 802.11a system selects various transmission speed between 6 and 54 Mbps according to the modulation mode. There are three typical methods for SNR estimation: Direct estimation method uses the frequency domain symbols to estimate SNR directly by minimizing MSE (Mean Square Error), EVM method utilizes the distance between the demodulated constellation points and received complex values, and the method utilizing the Viterbi algorithm uses the cumulative minimum distance in decoding process to estimate the SNR indirectly. Through comparison analyses of three methods we propose a new SNR estimation method, which employs both the EVM method and the Viterbi algorithm. Finally, we perform extensive computer simulations to confirm the performance improvement of the proposed adaptive OFDM systems on the basis of IEEE 802.11a.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8A
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• pp.671-678
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• 2005

This paper proposed symbol rate method which does not require a priori knowledge on the symbol rate and simplified modulation identification method to classify BPSK, QPSK, 8PSK signal. In order to estimate the unknown symbol rate, sliding FFT and simple moving average to estimate the spectrum of the signals is utilized, and sliding window and decimation, LPF blcok to estimate the proper symbol rate is used. Although conventional modulation ID method must use SNR value as the test statistics, the receiver cannot estimate the SNR value since the receiver cannot know the modulation type at the start of communication, and bit resolution is high due to using nonlinear function such as log, cosh. Therefore, we proposed the simplified fixed SNR value method. The performance of symbol rate estimation and modulation ID is shown using Monte Carlo computer simulation. This paper show that symbol rate estimation also has good performance in low SNR, and proposed simplified fixed SNR method has almost equivalent performance compared to conventional method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.101-107
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• 2011

The background noises and distortions by channel are major factors that disturb the practical use of speech recognition. Usually, noise reduce the performance of speech recognition system DSR(Distributed Speech Recognition) based speech recognition also bas difficulty of improving performance for this reason. Therefore, to improve DSR-based speech recognition under noisy environment, this paper proposes a method which detects accurate speech region to extract accurate features. The proposed method distinguish speech and noise by using entropy and detection of spectral energy of speech. The speech detection by the spectral energy of speech shows good performance under relatively high SNR(SNR 15dB). But when the noise environment varies, the threshold between speech and noise also varies, and speech detection performance reduces under low SNR(SNR 0dB) environment. The proposed method uses the spectral entropy and harmonics of speech for better speech detection. Also, the performance of AFE is increased by precise speech detections. According to the result of experiment, the proposed method shows better recognition performance under noise environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.76-82
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• 2010

In this paper, we analyze the performance of the block linear MMSE equalization for OFDM systems in doubly selective channels by computer simulations. The block linear MMSE equalization shows somewhat unusual BER characteristics in that the BER curve drops at first as SNR increases but then rises up as SNR increases further beyond some point. In this paper, we investigate the BER characteristics of the block linear MMSE equalization by analyzing the condition number of the coefficient matrix in the linear system involved in the equalization process, and propose a new method to avoid the BER performance degradation at high SNR.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.289-297
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• 2003

The performance of a bimodal system is affected by the accuracy of the endpoint detection from the input signal as well as the performance of the speech recognition or lipreading system. In this paper, we propose the endpoint detection method which detects the endpoints from the audio and video signal respectively and utilizes the signal to-noise ratio (SNR) estimated from the input audio signal to select the reliable endpoints to the acoustic noise. In other words, the endpoints are detected from the audio signal under the high SNR and from the video signal under the low SNR. Experimental results show that the bimodal system using the proposed endpoint detector achieves satisfactory recognition rates, especially when the acoustic environment is quite noisy.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.87.2-87.2
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• 2011

We report our 110 ks Chandra observations of the supernova remnant (SNR) 0104-72.3 in the Small Magellanic Cloud (SMC). The X-ray morphology shows two prominent lobes along the northwest-southeast direction and a soft faint arc in the east. Previous low resolution X-ray images attributed the unresolved emission from the southeastern lobe to a Be/X-ray star. Our high resolution Chandra data clearly shows that this emission is diffuse, shock-heated plasma, with negligible X-ray emission from the Be star. The eastern arc is positionally coincident with a filament seen in optical and infrared observations. Its X-ray spectrum is well fit by plasma of normal SMC abundances, suggesting that it is from shocked ambient gas. The X-ray spectra of the lobes show overabundant Fe, which is interpreted as emission from the reverse-shocked Fe-rich ejecta. The overall spectral characteristics of the lobes and the arc are similar to those of Type Ia SNRs, and we propose that SNR 0104-72.3 is the first case for a robust candidate Type Ia SNR in the SMC. On the other hand, the remnant appears to be interacting with dense clouds toward the east and to be associated with a nearby star-forming region. These features are unusual for a standard Type Ia SNR. Our results suggest an intriguing possibility that the progenitor of SNR 0104-72.3 might have been a white dwarf of a relatively young population.

• Journal of the Korean Society of Radiology
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• v.13 no.7
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• pp.961-968
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• 2019

The purpose of this study was to evaluate the usefulness of cerebral angiography in each energy level by using dual energy technique in CT. Methods were performed on 15 DE images and SE images of CT angiography. For the analysis of images, mean value, standard deviation, SNR and CNR value were determined by setting ROI on MCA, brain parenchyma tissue, and back ground. As a result of concurrent visual evaluation with Likert 5 point scale, the clearest MCA image was confirmed at DE 40 keV and SE 120 kVp(p>0.05). The SNR value of the SE image was measured to be similar to the 40 keV energy level of the DE image. The low energy level image of 40 keV and 50 keV was measured with a high SNR and the contrast ratio was higher than that of the high energy image.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, the forensic marking algorithm is proposed using psychoacoustic model II and MDCT for high-quality audio. The proposed forensic marking method, that inserts the user fingerprinting code of the audio content into the selected sub-band, in which audio signal energy is lower than the spectrum masking level. In the range of the one frame which has 2,048 samples for FFT of original audio signal, the audio forensic marking is processed in 3 sub-bands. According to the average attack of the fingerprinting codes, one frame's SNR is measured on 100% trace ratio of the collusion codes. When the lower strength 0.1 of the inserted fingerprinting code, SNR is 38.44dB. And in case, the added strength 0.5 of white gaussian noise, SNR is 19.09dB. As a result, it confirms that the proposed audio forensic marking algorithm is maintained the marking robustness of the fingerprinting code and the audio high-quality.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.43-45
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• 2018

Purpose In this study, we evaluated image by applying with and without point spread function algorithm(PSF) according to reconstruction type. Materials and Methods Biograph mMR (Siemens, Germany) was used as PET/MR scanner. For phantom study, we used NEMA IEC Body phantom maintaining radioactivity ratio (hotsphere:background = 8:1). To evaluate phantom image quality, percent contrast recovery and signal to noise ratio (SNR) were used by drawing ROI to 4 spheres. In clinical study, the 20 patients who underwent simultaneous PET/MR was selected and set the ROI at liver. we evaluated images as SNR. Results In the phantom results, The percent contrast recovery applying PSF algoritm was high 5 % compared to without PSF algoritm and SNR was also high 11 %. In the clinical study result, we confirmed that The SNR applying PSF algoritm was high 5 % compared to without PSF algoritm. Conclusion We need to simulate a lot of phantom study and clinical analysis to improve image quality for PET/MRI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.895-902
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• 2015

This paper presents a high-speed sensing and noise cancellation technique for large touch screens, which is called FDCS (Frequency Division Concurrent Sensing). Most conventional touch screen detection methods apply excitation pulses sequentially and analyze the sensing signals sequentially, and so are often unacceptably slow for large touch screens. The proposed technique applies sinusoidal signals of orthogonal frequencies simultaneously to all drive lines, and analyzes the signals from each sense line in frequency domain. Its parallel driving allows high speed detection even for a very large touch screens. It enhances the sensing SNR (Signal to Noise Ratio) by introducing a frequency domain noise filtering scheme. We also propose a pre-distortion equalizer, which compensates the drive signals using the inverse transfer function of touch screen panel to further enhance the sensing SNR. Experimental results with a 23" large touch screen show that the proposed technique enhances the frame scan rate by 273% and an SNR by 43dB compared with a conventional scheme.