• Title/Summary/Keyword: STFT

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Modeling of the Time-frequency Auditory Perception Characteristics Using Continuous Wavelet Transform (연속 웨이브렛 변환을 이용한 청각계의 시간-주파수 인지 특성 모델링)

  • 이상권;박기성;서진성
    • 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.

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Design and Implementation of a User-based MPI Checkpointer for Portability (이식성을 고려한 사용자기반 MPI 체크포인터의 설계 및 구현)

  • Ahn Sun-Il;Han Sang-Yong
    • Journal of KIISE:Computer Systems and Theory
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    • v.33 no.1_2
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    • pp.35-43
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    • 2006
  • An MPI Checkpointer is a tool which provides fault-tolerance through checkpointing The previous researches related to the MPI checkpointer have focused on automatic checkpointing and recovery capabilities, but they haven't considered portability issues. In this paper, we discuss design and implementation issues considered for portability when we developed an MPI checkpointer called STFT. In order to increase portability, firstly STFT supports the abstraction interface for a single process checkpointer. Secondly, STFT uses a user-based checkpointing method, and limits possible checkpointing places a user can make. Thirdly, STFT lets the MPI_Init create network connections to the other MPI processes in a fixed order. With these features, we expect STFT can be easily adaptable to various platforms and MPI implementations, and confirmed STFT is easily adaptable to LAM and MPICH/P4 with the prototype Implementation.

A Study on the Measuring EMG Signal Using Two-Dimensional images of the Fatigue analysis (2차원 영상을 이용한 근전도신호의 피로도 해석에 관한연구)

  • Kang, Byung-Jong;Lee, Young-Seock
    • Proceedings of the KAIS Fall Conference
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    • 2009.12a
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    • pp.1010-1013
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    • 2009
  • In this paper we propose the measurement of muscle fatigue using STFT(short time fourier transfom). The proposed method is time-frequency representation of muscle activity. We suggest that the proposed method can replace the classical muscle fatigue monitoring method using the median frequency.

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Use of a New Algorithm of the STFT with Variable Frequency Resolution for the Time-Frequency Auditory Model (청각계의 시간 및 주파수 특성을 고려한 VFR-STFT 알고리즘 제안)

  • Jeong, Hyuk;Ih, Jeong-Guon
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1998.06e
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    • pp.27-30
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    • 1998
  • 본 연구에서는 청각계의 시간 및 주파수 특성을 고려한 과도음의 시간-주파수 신호해석 기법인 VFT-STFT (STFT with Variable Frequency Resollution)을 제안하고자 한다. VFT-STFT은 downsampling와 FFT를 반복적으로 수행하여 주파수 대역에 따라 주파수 및 시간 분해능이 청각계의 특성과 유사한 기존의 VFR-FFT에 그 뿌리를 두고 있다. 그러나, 본 연구에서는 기존의 VFT-FFT 알고리즘에 overlap인자를 도입하여 시간-주파수 해석 결과를 구하고, 2/3-rate resampling에 의해 추가로 구성된 시간-주파수 해석 결과의 일부를 기존의 시간-주파수 해석 결과에 이식시킴으로서 기존의 VFT-FFT가 갖는 overlap과 spectral loss 등의 문제점을 최소화하고자 한다.

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Analysis Technique for the Vibration Signal of Revolution Machine Using the STFT (STFT를 이용한 회전체의 진동신호 분석 기법)

  • Park, Jong-Yeun;Park, Jun-Yong;Choi, Won-Ho
    • Journal of Industrial Technology
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    • v.24 no.A
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    • pp.67-73
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    • 2004
  • The purpose of this study is to analyze the vibration signal of the revolution machine using the STFT(Short Time Fourier Transform). It is common to analyze the frequency of signal through FFT algorithm with the fixed sampling rate. However, in this situation the order spectrum information useful rather than the general frequency information with the fixed sampling rate. In this paper, the resampling technique was used for getting the information of order spectrum. In resampling process, the arithmetic amount and MSE(Mean Square Error) for various kinds of the signal interpolation was compared and presented the propriety of the interpolation method while developing analysis equipment. Order tracking was implemented using signal interpolation method which it has selected. Then the analyzed results were obtained through simulation using the STFT technique.

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An Analysis of the Wave Propagation of a Structure Based on STFT, Higher Order Time-frequency Analysis and Wavelet Transform (STFT, 고차위그너분포 및 웨이브렛 변환 기술을 이용한 탄성파 추적)

  • 이상권
    • 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.

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Time-frequency Analysis of Train Vibration Using Order Analysis and Correlation (오더분석 및 상관관계를 활용한 철도차량 진동 데이터의 시간-주파수 분석)

  • Choi, Sung-Hoon;Igusa, Takeru;Park, Choon-Soo
    • Journal of the Korean Society for Railway
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    • v.12 no.6
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    • pp.989-995
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    • 2009
  • Short-time Fourier transforms (STFT) are useful for analyzing signals with harmonics that vary with time. If the variation of the harmonics with time is smooth, such as in kinematic vibrations in vehicles, then it is possible to improve the STFT using order spectra and correlation analysis. In this paper, it is shown how correlation analysis can be performed when the speed signal is noisy or unknown and then it is shown how order spectra become simple to compute after this analysis. The results are illustrated by an analysis of axle and car body vibrations in the prototype high-speed train, HSR-350x.

Implementation of Spectrum Sensing Module using STFT Method (STFT 기법을 적용한 스펙트럼 센싱 모듈 구현)

  • Lee, Hyun-So;Kang, Min-Kyu;Moon, Ki-Tak;Kim, Kyung-Seok
    • 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.

Analysis of Impulse Dispersion for IR-UWB Antenna Using Time-Frequency Analysis (시간-주파수 분석을 이용한 IR-UWB 안테나 임펄스 분산 특성 분석)

  • Koh, Young-Mok;Ra, Keuk-Hwan
    • 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.

Analyzing performance of time series classification using STFT and time series imaging algorithms

  • Sung-Kyu Hong;Sang-Chul Kim
    • 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.