• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11C
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• pp.1060-1067
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• 2005

In this paper, we generalize the shift-invariance properties of linear time-frequency distributions to the fractional Fourier domains that interpolate between the time and frequency domains. Magnitude-wise shift invariance in arbitrary fractional Fourier domains distinguishes the short-time Fourier transform (STFT) among all linear time-frequency distributions and simplifies the interpretation of the resultant distribution. We prove that the STFT is the only linear distribution that satisfies the magnitude-wise shift-invariance property in the fractional Fourier domains.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.3
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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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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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.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.78-86
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• 2010

The Spectrum Sensing Technology is the core technology of the Cognitive Radio (CR) System that is one of the future wireless communication technologies. In this paper, we proposed the efficient Spectrum Sensing Method using the Short Time Fourier Transform (STFT) that is the algorithm for Time-Frequency analysis of the raw data. Applied window function to STFT algorithm is a Kaiser window, it is piled up its 50% range. For the simulation, the 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. And also, Spectrum Sensing Module is implemented using embedded board.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.4
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• pp.270-276
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• 1999

Fourier transform has been one of the most commonly used tools in study of frequency characteristics of signal. However, based on the Fourier transform. it is hard to tell whether a signal's frequency contents evolve in time or not. Recently, to overcome Fourier transform fault. not to represent non-stationary signal, time-frequency analysis methods are developed and those can represent informations of signal's time and frequency at the same time. In this study we analysed ultrasonic signal for degraded SUS 316 with time-frequency analysis method. In particular the methods such as short time Fourier(STFT) and Wigner-Ville distribution(WVD) were used to extract frequency contents and characteristics from ultrasonic signals.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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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)

• Proceedings of the KIEE Conference
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• 2002.07c
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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.