• 한국통신학회논문지
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• 제30권11C호
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• pp.1060-1067
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• 2005

시간 영역과 주파수 영역을 사이의 공간을 뜻하는 부분 푸리에 영역으로 (fractional Fourier domains) 선형 시간-주파수 분포의 옮김 불변 특성을 일반화한다. 다른 선형 사주파수 분포와 달리 짧은 시간 푸리에 변환은(short time Fourier transform: STFT) 부분 푸리에 영역에서 크기 (magnitude-wise) 옮김 불변을 지니는데, 이 짧은 시간 푸리에 변환을 쓰면 분포를 좀더 쉽게 해석할 수 있다. 특히, 부분 푸리에 영역에서 크기 옮김 불변인 선형 분포는 짧은 시간 푸리에 변환뿐이라는 것을 밝힌다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 추계학술대회
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• pp.375-378
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• 2009

The Spectrum Sensing Technology is the core technology of the Cognitive Radio (CR) System that is one of the future wireless communication technologies. This is the technology that temporarily allocates the frequency bandwidth by scanning surrounding wireless environments to keep licensed terminals and search the unused frequency bandwidth. In this paper, we proposed the efficient Spectrum Sensing Method using the Short Time Fourier Transform (STFT). The Cosine and DVB-H signal with the 6MHz bandwidth is used as the Input Signal. And we confirm the Spectrum Sensing result using Modified Periodogram Method, Welch's Method for compared with Short Time Fourier Transform Algorithm.

• 한국생산제조학회지
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• 제19권3호
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• pp.407-413
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• 2010

This paper reports on the research which analyzes acoustic signals acquired in progressive compressing, hole blanking, and burr compacting process. An acoustic sensor was set on the bed of hydraulic press. Acoustic signal is generated from progressive stamping process. First the signal acquired from the unit process; compressing, blanking or compacting, is studied by Fourier Transform and Short Time Fourier Transform. The blanking process emitted ultrasonic signal with more than 20kHz, but the compressing and compacting processes emitted acoustic signals with lower than 10kHz. The combined signals periodically acquired right after the tool grinding were then analyzed. 70-80kHz signals appeared in time-frequency domain, but not in the frequency domain, the magnitude of which was related to the tool wear. Short Time Fourier Transform made up for the Fourier Transform in analyzing the emitted signal for stamping process in the ultrasonic domain.

• 한국소음진동공학회논문집
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• 제15권3호
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• pp.266-271
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• 2005

Although time-frequency analysis is useful for dispersive wave analysis, conventional methods such as the short-time Fourier transform do not take the dispersion phenomenon into consideration in the tiling of the time-frequency domain. The objective of this paper is to develop an adaptive time-frequency analysis method whose time-frequency tiling is determined with the consideration of signal dispersion characteristics. To achieve the adaptive time-frequency tiling, each of time-frequency atoms is rotated in the time-frequency plane depending on the local wave dispersion. To carry out this adaptive time-frequency transform, dispersion characteristics hidden in a signal are first estimated by an iterative scheme. To examine the effectiveness of the present method, the flexural wave signals measured in a plate were analyzed.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.606-610
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• 2004

Although time-frequency analysis is useful for dispersive wave analysis, conventional methods such as the short-time Fourier transform do not take the dispersion phenomenon into consideration in the tiling of the time-frequency domain. The objective of this paper is to develop an adaptive time-frequency analysis method whose time-frequency tiling is determined with the consideration of signal dispersion characteristics. To achieve the adaptive time-frequency tiling, each of time-frequency atoms is rotated in the time-frequency plane depending on the local wave dispersion. To carry out this adaptive time-frequency transform, dispersion characteristics hidden in a signal are first estimated by an iterative scheme. To examine the effectiveness of the proposed method, the flexural wave signals measured in a plate were analyzed.

• 한국콘텐츠학회논문지
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• 제10권1호
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• pp.78-86
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• 2010

스펙트럼 센싱 기술은 차세대 무선통신 기술들 중 하나인 Cognitive Radio (CR) 시스템에서의 핵심 기술이다. 본 논문은 CR 기술 기반의 효율적인 스펙트럼 센싱을 위하여 대상 신호의 시간-주파수 측면의 분석을 위한 알고리즘인 Short Time Fourier Transform을 적용하는 방법을 제안하였다. STFT에 적용된 윈도우는 Kaiser Window이며, 그 중첩 정도는 50%로 규정하였다. 시뮬레이션을 위해 6MHz 대역폭을 가진 DVB-H 신호를 입력 신호로 하였으며, Modified Periodogram Method, Welch's Method와의 비교를 통하여 제안한 알고리즘의 성능을 확인하였다. 또한, 임베디드 보드를 통하여 스펙트럼 센싱 모듈을 구현하였다.

• 비파괴검사학회지
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• 제19권4호
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• pp.270-276
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• 1999

지금까지 퓨리에 변환이 신호처리법으로 가장 널리 사용되고 있다. 그러나, 이 방법은 신호의 주파수성분이 시간에 대하여 어떻게 변화하는지를 표현하지 못한다. 따라서, 최근 이와 같이 비정상신호를 표현하지 못하는 퓨리에 변환의 단점을 보완하여, 신호의 시간과 주파수에 대한 정보를 동시에 표현할 수 있는 시간-주파수 해석법들이 개발되기 시작하였다. 본 연구에서는 인공열화된 SUS 316강의 초음파신호를 시간-주파수 해석법으로 분석하였다. 특히, 단시간 퓨리에 변화법과 위그너 빌 분포법을 이용하여 초음파 신호의 주파수 성분과 특성을 분석하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.428-433
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• 2002

There have been many studies to visualize the vibration and noise of rotary compressor. Most of these studies assumed that the signal is stationary and the time-averaged signal is used for visualization. However, the noise and vibration signals generated during one cycle of crank shaft vary continuously. In this paper, the noise and vibration of rotary compressor which vary continuously are visualized by short time fourier transform method. The location of source and the transfer path of vibration and noise at arbitrary frequencies, which can not be visualized by averaged signal, can be visualized clearly.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문초록집
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• pp.346.1-346
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• 2002

There have been many studies to visualize the vibration and noise of rotary compressor. Most of these studies assumed that the signal is stationary and the time-averaged signal is used for visualization. However, the noise and vibration signals generated during one cycle of crank shaft vary continuously. In this paper, the noise and vibration of rotary compressor which vary continuously are visualized by short time fourier transform method. (omitted)

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 C
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• pp.1871-1873
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• 2002

Partial Discharge is radiated in the form of electromagnetic wave from variable sources. It can be taken by UHF antenna and the signal pulse from that has a nonstationary time-series which can be evaluated with several methods. One of them is STFT(short time fourier transform) processed in frequency region. Statistical results using STFT show the possibility being able to discriminate between several PD sources.