• Title/Summary/Keyword: Time Spectral method

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Analysis of Commute Time Embedding Based on Spectral Graph (스펙트럴 그래프 기반 Commute Time 임베딩 특성 분석)

  • Hahn, Hee-Il
    • Journal of Korea Multimedia Society
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    • v.17 no.1
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    • pp.34-42
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    • 2014
  • In this paper an embedding algorithm based on commute time is implemented by organizing patches according to the graph-based metric, and its performance is analyzed by comparing with the results of principal component analysis embedding. It is usual that the dimensionality reduction be done within some acceptable approximation error. However this paper shows the proposed manifold embedding method generates the intrinsic geometry corresponding to the signal despite severe approximation error, so that it can be applied to the areas such as pattern classification or machine learning.

Analysis method for the Measured Track Geometry Data using Wavelet Transform (웨이브렛 변환을 이용한 궤도틀림 분석)

  • Lee, In-Kyu;Kim, Sung-Il;Yeo, In-Ho
    • Journal of the Korean Society for Railway
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    • v.9 no.2 s.33
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    • pp.187-192
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    • 2006
  • The regularity of railway track alignment is a crucial component fur maintaining travel safety and the smoothness of passenger ride. The conventional spectral analysis has been considered to estimate the severity of the track irregularity from measured data. The time domain data used to be changed into the frequency domain by Fourier transform. Because the measuring points can be regarded as the time points, the spatial-frequency can be introduced instead of the time-frequency. Although FFT(Fast Fourier Transform) and/or PSD(Power Spectral Density) function could provide fairly localized information within frequency domain, but chronical configurations of data could be missed. In this study, we attempt to apply the Morlet wavelet transform for the purpose of a frequency-time-domain analysis rather than a frequency-domain analysis. The applicability of wavelet transform is examined for the estimation of the track irregularity with real measured track data on the section of Kyoung-bu line by EM-120 measuring vehicle. It is shown that the wavelet transform can be an effective tool to manage the track irregularity.

Development of a Reliable Real-time 3D Reconstruction System for Tiny Defects on Steel Surfaces (금속 표면 미세 결함에 대한 신뢰성 있는 실시간 3차원 형상 추출 시스템 개발)

  • Jang, Yu Jin;Lee, Joo Seob
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.12
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    • pp.1061-1066
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    • 2013
  • In the steel industry, the detection of tiny defects including its 3D characteristics on steel surfaces is very important from the point of view of quality control. A multi-spectral photometric stereo method is an attractive scheme because the shape of the defect can be obtained based on the images which are acquired at the same time by using a multi-channel camera. Moreover, the calculation time required for this scheme can be greatly reduced for real-time application with the aid of a GPU (Graphic Processing Unit). Although a more reliable shape reconstruction of defects can be possible when the numbers of available images are increased, it is not an easy task to construct a camera system which has more than 3 channels in the visible light range. In this paper, a new 6-channel camera system, which can distinguish the vertical/horizontal linearly polarized lights of RGB light sources, was developed by adopting two 3-CCD cameras and two polarized lenses based on the fact that the polarized light is preserved on the steel surface. The photometric stereo scheme with 6 images was accelerated by using a GPU, and the performance of the proposed system was validated through experiments.

Running Monitoring by the Noise and Vibration Measurement near the Wheelset of the High-Speed Trains : A Preliminary Research (고속철도차량 윤축부근의 소음과 진동 측정을 통한 주행중 감시의 기초연구)

  • Lee, Jun-Seok;Choi, Sung-Hoon;Park, Choon-Soo
    • Proceedings of the KSR Conference
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    • 2008.11b
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    • pp.1454-1462
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    • 2008
  • This paper is focused on the analysis of the noise and vibration measured near the wheelset of the high-speed trains using a time-varying frequency transform as a preliminary research of running monitoring. Due to the non-stationary characteristics, it is necessary to examine noise and vibration of the train with time-varying frequency transforms. In this paper, the short-time Fourier transform method is utilized - the stored data is localized by modulating with a window function, and Fourier transform is taken to each localized data. For the examination, the non-stationary noise and vibration of the high-speed train's wheelset are measured by using some microphones and accelerometers, and those signals are stored in a on-board data acquisition system. The non-stationary random signal analyses with the short-time Fourier transform are performed, and the result are classified as follows; auto-spectral density, cross-spectral density, frequency response, and coherence functions. From those functions, it is possible to observe the frequency characteristics of sleepers, switchers, tunnels, and steel bridges. Also, some distinct peaks, which are not dependent upon the train's speed, are identified from the results.

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A Study on the Improvement of Image Fusion Accuracy Using Smoothing Filter-based Replacement Method (SFR기법을 이용한 영상 융합의 정확도 향상에 관한 연구)

  • Yun Kong-Hyun
    • Spatial Information Research
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    • v.14 no.1 s.36
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    • pp.85-94
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    • 2006
  • Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

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Optimally Weighted Cepstral Distance Measure for Speech Recognition (음성 인식을 위한 최적 가중 켑스트랄 거리 측정 방법)

  • 김원구
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06c
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    • pp.133-137
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    • 1994
  • In this paper, a method for designing an optimal weight function for the weighted cepstral distance measure is proposed. A conventional weight function or cepstral lifter is obtained eperimentally depending on the spectral components to be emphasized. The proposed method minimizes the error between word reference patterns and the traning data. To compare the proposed optimal weight function with conventional function, speech recognition systems based on Dpynamic Time Warping and Hidden Markov Models were constructed to conduct speaker independent isolated word necogination eperiment. Results show that the proposed method gives better performance than conventional weight functions.

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Estimating Amino Acid Composition of Protein Sequences Using Position-Dependent Similarity Spectrum (위치 종속 유사도 스펙트럼을 이용한 단백질 서열의 아미노산 조성 추정)

  • Chi, Sang-Mun
    • Journal of KIISE:Software and Applications
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    • v.37 no.1
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    • pp.74-79
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    • 2010
  • The amino acid composition of a protein provides basic information for solving many problems in bioinformatics. We propose a new method that uses biologically relevant similarity between amino acids to determine the amino acid composition, where the BOLOSUM matrix is exploited to define a similarity measure between amino acids. Futhermore, to extract more information from a protein sequence than conventional methods for determining amino acid composition, we exploit the concepts of spectral analysis of signals such as radar and speech signals-the concepts of time-dependent analysis, time resolution, and frequency resolution. The proposed method was applied to predict subcellular localization of proteins, and showed significantly improved performance over previous methods for amino acid composition estimation.

HIGHER ORDER OPERATOR SPLITTING FOURIER SPECTRAL METHODS FOR THE ALLEN-CAHN EQUATION

  • SHIN, JAEMIN;LEE, HYUN GEUN;LEE, JUNE-YUB
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.21 no.1
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    • pp.1-16
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    • 2017
  • The Allen-Cahn equation is solved numerically by operator splitting Fourier spectral methods. The basic idea of the operator splitting method is to decompose the original problem into sub-equations and compose the approximate solution of the original equation using the solutions of the subproblems. The purpose of this paper is to characterize higher order operator splitting schemes and propose several higher order methods. Unlike the first and the second order methods, each of the heat and the free-energy evolution operators has at least one backward evaluation in higher order methods. We investigate the effect of negative time steps on a general form of third order schemes and suggest three third order methods for better stability and accuracy. Two fourth order methods are also presented. The traveling wave solution and a spinodal decomposition problem are used to demonstrate numerical properties and the order of convergence of the proposed methods.

Improving Speech/Music Discrimination Parameter Using Time-Averaged MFCC (MFCC의 단구간 시간 평균을 이용한 음성/음악 판별 파라미터 성능 향상)

  • Choi, Mu-Yeol;Kim, Hyung-Soon
    • MALSORI
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    • no.64
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    • pp.155-169
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    • 2007
  • Discrimination between speech and music is important in many multimedia applications. In our previous work, focusing on the spectral change characteristics of speech and music, we presented a method using the mean of minimum cepstral distances (MMCD), and it showed a very high discrimination performance. In this paper, to further improve the performance, we propose to employ time-averaged MFCC in computing the MMCD. Our experimental results show that the proposed method enhances the discrimination between speech and music. Moreover, the proposed method overcomes the weakness of the conventional MMCD method whose performance is relatively sensitive to the choice of the frame interval to compute the MMCD.

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Band Selection Algorithm based on Expected Value for Pixel Classification (픽셀 분류를 위한 기댓값 기반 밴드 선택 알고리즘)

  • Chang, Duhyeuk;Jung, Byeonghyeon;Heo, Junyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.107-112
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    • 2022
  • In an embedded system such as a drone, it is difficult to store, transfer and analyze the entire hyper-spectral image to a server in real time because it takes a lot of power and time. Therefore, the hyper-spectral image data is transmitted to the server through dimension reduction or compression pre-processing. Feature selection method are used to send only the bands for analysis purpose, and these algorithms usually take a lot of processing time depending on the size of the image, even though the efficiency is high. In this paper, by improving the temporal disadvantage of the band selection algorithm, the time taken 24 hours was reduced to around 60-180 seconds based on the 40000*682 image resolution of 8GB data, and the use of 7.6GB RAM was significantly reduced to 2.3GB using 45 out of 150 bands. However, in terms of pixel classification performance, more than 98% of analysis results were derived similarly to the previous one.