• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.827-832
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• 2003

There has been a number methods for the presentation of time-frequency analysis of non-stationary signal. In this paper, STFT(short time Fourier transform), wavelet transform, Wigner distribution, and higher order Wigner distribution are discussed in details with simulation signals. They are also applied to the analysis of the wave propagation of a semi finite beam. Wigner distribution and higher order Wigner distribution have good time-frewuency resolutions. Wavelet transform is required for impact analysis but should be applied carefully. STFT suffers from time-frequency resolutions. Each method is has its advantage and disadvantage depending on each application signals.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.1-11
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• 2023

In this paper, instead of using recurrent neural network, we compare a classification performance of time series imaging algorithms using convolution neural network. There are traditional algorithms that imaging time series data (e.g. GAF(Gramian Angular Field), MTF(Markov Transition Field), RP(Recurrence Plot)) in TSC(Time Series Classification) community. Furthermore, we compare STFT(Short Time Fourier Transform) algorithm that can acquire spectrogram that visualize feature of voice data. We experiment CNN's performance by adjusting hyper parameters of imaging algorithms. When evaluate with GunPoint dataset in UCR archive, STFT(Short-Time Fourier transform) has higher accuracy than other algorithms. GAF has 98~99% accuracy either, but there is a disadvantage that size of image is massive.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1393-1401
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• 2019

Recently as voice authentication function is installed in the system, it is becoming more important to accurately authenticate speakers. Accordingly, a model for verifying speakers in various ways has been suggested. In this paper, we propose a new method for verifying speaker verification using a Short-time Fourier Transform(STFT). Unlike the existing Mel-Frequency Cepstrum Coefficients(MFCC) extraction method, we used window function with overlap parameter of around 66.1%. In this case, the speech characteristics of the speaker with the temporal characteristics are studied using a deep running model called RNN (Recurrent Neural Network) with LSTM cell. The accuracy of proposed model is around 92.8% and approximately 5.5% higher than that of the existing speaker certification model.

• 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.

• Journal of the Korean Geotechnical Society
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• v.36 no.10
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• pp.41-56
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• 2020

For the rapid and accurate warning, the system requires not only the sufficient number of seismometers but also the appropriate detection technique of sensor data. Instead of installing new seismometers, on-board accelerometers of the train could be utilized as alternatives. However, the data from on-board accelerometers includes train vibrations and the response of embankment site by earthquake, which are different from earthquakes measured from the seismometer. This study suggests signal analysis technique to detect earthquake from the on-board accelerometer data. The virtual on-board accelerometer data including the response of embankment site, obtained from site response analysis method, has been constructed. The constructed data has been analyzed using short time Fourier transform (STFT) and wavelet transform (WT). STFT method provides better performance to detect long-period earthquake whereas WT method is more available to detect short-period earthquake.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.81-87
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• 2001

The human auditory system is appropriate for the "constant Q"system. The STFT (Short Time Fourier Transform) is not suitable for the auditory perception model since it has constant bandwidth. In this paper, the CWT (continuous wavelet transform) is employed for the auditory filter model. In the CWT, the frequency resolution can be adjusted for auditory sensation models. The proposed CWT is applied to the modeling of the JNVF. In addition, other signal processing methods such as STFT, VER-FFT and VFR-STFT are discussed. Among these methods, the model of JNVF (Just Noticeable Variation in Frequency) by using the CWT fits in with the JNVF of auditory model although it requires quite a long time.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.12
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• pp.1371-1379
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• 2010

This paper presents an analysis of impulse dispersion for impulse radio ultra-wide band(IR-UWB) antenna. A set of antenna structure configurations are highlighted with verification based on the STFT(Short Time Fourier Transform) in 3.1~5.1 GHz: first, a taper-slotted antenna allowing the optimal impulse transmission, and second, 4 types of the omni-directional IR-UWB antenna using different feed structures(microstrip line, and CPW(Coplanar Waveguide)). The proposed STFT allows the analysis of the IR-UWB antenna's dispersion characteristic.