• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.18-26
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• 2015

In this paper, we studied the method for analyzing and estimating the parameters that induce I/Q imbalance in the repeater using direct conversion RF. In repeater, amplitude, phase, and filter mismatch are generated in the receiving-end which converts RF signal to baseband signal. And amplitude and phase mismatch are generated in the transmitting-end which converts baseband signal to RF signal. Accordingly, we modeled the parameters that cause I/Q imbalance in the structure of the repeater in order, and proposed a feedback test structure from the transmitting-end to the receiving-end for estimating the corresponding parameters. By comparing the test transmitting signal and received signal, it is possible to estimate the I/Q imbalance parameters which occurred from mixed components of real and imaginary part. And it was confirmed that I/Q imbalance phenomenon has been properly compensated with estimated parameters at the direct conversion RF repeater.

• Science of Emotion and Sensibility
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• v.7 no.2
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• pp.141-148
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• 2004

This paper proposed a new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in cA3 and weighted cDl. cA3 coefficients represent the voiced sound with low frequency and cDl coefficients represent the unvoiced sound with high frequency. From simulation results, it is demonstrated that the proposed algorithm improves SNR and MSE performance more than Wavelet transform and Wavelet packet transform does. Moreover, the reconstructed signals by the proposed algorithm resemble the original signal in terms of plosive sound, fricative sound and affricate sound but Wavelet transform and Wavelet packet transform reduce those sounds seriously.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.501-510
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• 2000

Recently, advanced signal analysis which is called "time-frequency analysis" has been used widely in nondestructive evaluation applications. Wavelet transform(WT) and Wigner Distribution are the most advanced techniques for processing signals with time-varying spectra. Wavelet analysis method is an attractive technique for evaluation of material characterization nondestructively. Wavelet transform is applied to the time-frequency analysis of ultrasonic echo waveform obtained by an ultrasonic pulse-echo technique. In this study, the feasibility of noise suppression of ultrasonic flaw signal and frequency-dependent ultrasonic group velocity and attenuation coefficient using wavelet analysis of ultrasonic echo waveform have been verified experimentally. The Gabor function is adopted the analyzing wavelet. The wavelet analysis shows that the variations of ultrasonic group velocity and attenuation coefficient due to the change of material characterization can be evaluated at each frequency. Furthermore, to assure the enhancement of detectability and naw sizing performance, both computer simulated results and experimental measurements using wavelet signal processing are used to demonstrate the effectiveness of the noise suppression of ultrasonic flaw signal obtained from austenitic stainless steel weld including EDM notch.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.5
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• pp.501-509
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• 2011

Software defined radio(SDR) has a goal that places the analog-to-digital converter(ADC) as near the antenna as possible. But current technique actually can't do analog-to-digital converting about RF band signals. So one method is studying that samples RF band signals to IF band. One of the ways Sub-Sampling technique can convert signals from RF band to IF band without oscillator. If Sub-Sampling technique is used, over 2 bands can convert signals from RF band to IF band. But due to the filter performance in RF band, it is possible to generate interference between signals that is converted in low frequency band. The effect degrades performance. In this paper, we propose one method that uses time division multiplexing(TDM) method as a solution to avoid interference between signals. By doing TDM and Sub-Sampling at the same time that method can get signals without large changes of structures.

• Progress in Medical Physics
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• v.10 no.3
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• pp.141-149
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• 1999

This research analyzed the HRV signals by using wavelet transform to observe the activities of autonomous nervous system in a sleep state. This research also restructured the HRV signals from electrocardiogram and by using coefficient which was obtained through wavelet transform, analyzed the signals by frequency bandwidth. Then compared the analyzed results with existing frequency analyzing method using AR model techniques. The suggested wavelet coefficient from power spectrum component in the study shows a similar tendency with the results from FFT or AR model technique. Therefore, it can be found that power spectrum analyzing method by wavelet coefficient is a useful as a tool for analyzing autonomous nervous system activities using HRV signals. Since the suggested method able to clearly depict the progression of change in time zone, which was once impossible with the existing methods, it is presumed that it will be useful in other physiological signals.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.5
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• pp.34-40
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• 1994

콘베어 계량대 위에서 이동간 계량은 A/D변환된 데이터의 신속하고 안정된 처리가 요구된다. 또한 중량의 측정은 다른 센서와 달리 여러 가지 고려요소가 많이 있다. 본 연구에서는 자동계량 콘베어 설비에서 보다 신속하고 안정된 계량데이타를 얻기 위한 신호처리 방법을 제안하다. 먼저 콘베어 계량대에서의 로드셀중량센서신호의 특성을 분석하고 시뮬레이션과 실측으로 고유진동주파수를 구하여 저역 통과필터를 설계하였으며, A/D변환 회로를 구성하여 A/D변환된 데이터의 안정화처리 알고리즘을 싱글칩 마이크로프로세서를 이용하여 구현하였다. 제안된 방법을 이용하여 실제 제작하여 실측해 본 결과 계량 속도와 A/D 변환의 안정성에서 만족스러운 결과를 얻었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.1016-1021
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• 1999

In order to obtain a demodulated signal from RZ-SSB signal, it is important to design a linearizer which cancels the high-order distortions after FM demodulation. Since the NTT's linearizer must include a Hilbert transform, the characteristics of the linearizer are determined by the characteristics of Hilbert transform and it is very complicated to design and realize especially in the low frequency range. In the case of the proposed linearizer, the high-order distortion can be reduced without using any Hilbert transform. Furthemore, unlike the conventional RZ-SSB Demodulator, the proposed linearizer can be realized easily.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2758-2760
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• 2002

패턴 인식(Patterns Recognition)은 인공 지능의 한 분야로서 이해할 수 있는데, 요즈음은 보안과 관련하여 많은 연구가 진행되고 있다. 웨이블렛 변환(Wavelet Transform)은 푸리에 변환에 기반을 둔 기존의 알고리즘에 비해 시간-주파수 영역에서 신호의 국소화를 효율적으로 구현할 수 있다. 하지만, 이를 패턴 인식의 특징 추출에 그대로 이용할 경우 입력 신호의 위치 이동 등이 문제가 되며, 이것은 또한 에러 요인이 된다. 본 연구에서는 웨이블렛 변환을 패턴 인식에 적용할 경우, 입력 신호의 위치 이동 등이 있는 경우 생기는 문제점을 보완하여, 개선된 방법으로 패턴 인식에 사용할 수 있는 알고리즘을 제안하며, 실험 결과를 토대로 그의 타당성을 보인다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.71-76
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• 1999

In digital cellular communication systems, tandem coding occurs in communications between mobile phones with different speech codecs, resulting in poor voice quality, high computational load, and long transmission delay. In this paper, voice packet conversion technique is proposed to solve the tandem coding problems, and packet conversion algorithm from 13kbps QCELP to 8kbps QCELP is developed. Simulations using various speech data show that the proposed packet conversion method produces voice quality which is equivalent to that by the conventional tandem coding method with shorter transmission delay using about 33% computational load.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.281-286
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• 2003

Wavelet Transform can effectively represent the local characteristics of a signal in the space-frequency domain. However, the feature vector extracted using wavelet transform is not translation invariant. This paper describes a new feature extraction method using wavelet transform, which is translation-invariant. Based on this translation-invariant feature extraction, the iris recognition method, based on this feature extraction method, is robust to noises. Experimentally, we show that the proposed method produces super performance in iris recognition.