• 제목/요약/키워드: Linear Spectral

검색결과 579건 처리시간 0.034초

Damage detection of bridges based on spectral sub-band features and hybrid modeling of PCA and KPCA methods

  • Bisheh, Hossein Babajanian;Amiri, Gholamreza Ghodrati
    • Structural Monitoring and Maintenance
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    • 제9권2호
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    • pp.179-200
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    • 2022
  • This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T2 and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

A New Calibration Method Based on the Recursive Linear Regression with Variables Selection

  • Park, Kwang-Su;Jun, Chi-Hyuck
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1241-1241
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    • 2001
  • We propose a new calibration method, which uses the linearization method for spectral responses and the repetitive adoptions of the linearization weight matrices to construct a frature. Weight matrices are estimated through multiple linear regression (or principal component regression or partial least squares) with forward variable selection. The proposed method is applied to three data sets. The first is FTIR spectral data set for FeO content from sinter process and the second is NIR spectra from trans-alkylation process having two constituent variables. The third is NIR spectra of crude oil with three physical property variables. To see the calibration performance, we compare the new method with the PLS. It is found that the new method gives a little better performance than the PLS and the calibration result is stable in spite of the collinearity among each selected spectral responses. Furthermore, doing the repetitive adoptions of linearization matrices in the proposed methods, uninformative variables are disregarded. That is, the new methods include the effect of variables subset selection, simultaneously.

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Fatigue life prediction of horizontally curved thin walled box girder steel bridges

  • Nallasivam, K.;Talukdar, Sudip;Dutta, Anjan
    • Structural Engineering and Mechanics
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    • 제28권4호
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    • pp.387-410
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    • 2008
  • The fatigue damage accumulation rates of horizontally curved thin walled box-girder bridge have been estimated from vehicle-induced dynamic stress history using rain flow cycle counting method in the time domain approach. The curved box-girder bridge has been numerically modeled using computationally efficient thin walled box-beam finite elements, which take into account the important structural actions like torsional warping, distortion and distortional warping in addition to the conventional displacement and rotational degrees of freedom. Vehicle model includes heave-pitch-roll degrees of freedom with longitudinal and transverse input to the wheels. The bridge deck unevenness, which is taken as inputs to the vehicle wheels, has been assumed to be a realization of homogeneous random process specified by a power spectral density (PSD) function. The linear damage accumulation theory has been applied to calculate fatigue life. The fatigue life estimated by cycle counting method in time domain has been compared with those found by estimating the PSD of response in frequency domain. The frequency domain method uses an analytical expression involving spectral moment characteristics of stress process. The effects of some of the important parameters on fatigue life of the curved box bridge have been studied.

Linear Spectral Mixture Analysis of Landsat Imagery for Wetland land-Cover Classification in Paldang Reservoir and Vicinity

  • Kim, Sang-Wook;Park, Chong-Hwa
    • 대한원격탐사학회지
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    • 제20권3호
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    • pp.197-205
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    • 2004
  • Wetlands are lands with a mixture of water, herbaceous or woody vegetation and wet soil. And linear spectral mixture analysis (LSMA) is one of the most often used methods in handling the spectral mixture problem. This study aims to test LSMA is an enhanced routine for classification of wetland land-covers in Paldang reservoir and vicinity (paldang Reservoir) using Landsat TM and ETM+ imagery. In the LSMA process, reference endmembers were driven from scatter-plots of Landsat bands 3, 4 and 5, and a series of endmember models were developed based on green vegetation (GV), soil and water endmembers which are the main indicators of wetlands. To consider phenological characteristics of Paldang Reservoir, a soil endmember was subdivided into bright and dark soil endmembers in spring and a green vegetation (GV) endmember was subdivided into GV tree and GV herbaceous endmembers in fall. We found that LSMA fractions improved the classification accuracy of the wetland land-cover. Four endmember models provided better GV and soil discrimination and the root mean squared (RMS) errors were 0.011 and 0.0039, in spring and fall respectively. Phenologically, a fall image is more appropriate to classify wetland land-cover than spring's. The classification result using 4 endmember fractions of a fall image reached 85.2 and 74.2 percent of the producer's and user's accuracy respectively. This study shows that this routine will be an useful tool for identifying and monitoring the status of wetlands in Paldang Reservoir.

선형 위상 신호를 이용한 위상속도 측정에 관한 연구 (A Study on Phase Velocity Measurement using Linear Phase Signal)

  • 고덕영;김계국;이종악
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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    • pp.51-54
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    • 1988
  • In this paper, Digital signal processing method is deserved by the tissue characteristic quantization. Linear phase velocity is studied using linear signal, and the slope which attenuation characteristics are decreased is analysed according to frequency increase. A more efficient method determining the minimum phase function is developed from the spectral magnitud function.

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화자 적응 방법들의 비교 (The Comparison of Speaker Adaptation Methods)

  • 황영수
    • 한국음향학회지
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    • 제18권1호
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    • pp.61-66
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    • 1999
  • 본 논문은 화자 적응 방법 제안과 그 방법들의 성능을 검토한 것이다. 본 논문에서 제안 검토한 방법들은 최대사후확률추정(MAPE)방법, 음성 선형 특성을 이용한 방법, 다층 퍼셉트론(MLP)을 이용한 방법과 ARTMAP을 이용한 방법들이다. 각 방법들의 성능 평가를 위하여 한국어 숫자음으로 실험한 결과, 최대사후확률추정 방법과 반연속 HMM의 출력 확률적응, 음성 선형 특성 등 3방법을 결합한 방법이 가장 우수한 결과를 보였으며, 이와 비슷한 실험 결과를 ARTMAP을 이용한 화자 적응 방법에서 보였다.

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Bootstrap methods for long-memory processes: a review

  • Kim, Young Min;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • 제24권1호
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    • pp.1-13
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    • 2017
  • This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

스펙트럼 추정을 이용한 탄성파 트레이스 내삽 (Seismic Trace Interpolation using Spectral Estimation)

  • 지준
    • 지구물리와물리탐사
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    • 제6권3호
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    • pp.134-137
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    • 2003
  • 본 본문은 탄성파 자료에서 흔히 볼 수 있는 선형이벤트에 대한 내삽 기법을 소개하고 있다. 선형이벤트를 갖고 있는 2차원 자료의 경우, 내삽을 수행한 후의 스펙트럼의 모양은 내삽하기 전의 알리아싱(aliasing)된 스펙트럼의 모양으로부터 추정이 가능하다. 측정되지 않은 트레이스의 복원은 특정 필터를 적용한 결과의 전체 에너지가 최소화 되도록 구해지게 되며 이때 사용되는 필터의 진폭 스펙트림은 추정된 스펙트럼의 역(inverse)에 해당된다.

Optimal Waveform Design for Ultra-Wideband Communication Based on Gaussian Derivatives

  • Guo, Yong
    • Journal of Communications and Networks
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    • 제10권4호
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    • pp.451-454
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    • 2008
  • Ultra-wideband (UWB) radios have attracted great interest for their potential application in short-range high-data-rate wireless communications. High received signal to noise ratio and compliance with the Federal Communications Commissions (FCC) spectral mask call for judicious design of UWB pulse shapers. In this paper, even and odd order derivatives of Gaussian pulse are used respectively as base waveforms to produce two synthesized pulses. Our method can realize high efficiency of spectral utilization in terms of normalized effective signal power (NESP). The waveform design problem can be converted into linear programming problem, which can be efficiently solved. The waveform based on even order derivatives is orthogonal to the one based on odd order derivatives.

GMM based Nonlinear Transformation Methods for Voice Conversion

  • Vu, Hoang-Gia;Bae, Jae-Hyun;Oh, Yung-Hwan
    • 대한음성학회:학술대회논문집
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    • 대한음성학회 2005년도 추계 학술대회 발표논문집
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    • pp.67-70
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    • 2005
  • Voice conversion (VC) is a technique for modifying the speech signal of a source speaker so that it sounds as if it is spoken by a target speaker. Most previous VC approaches used a linear transformation function based on GMM to convert the source spectral envelope to the target spectral envelope. In this paper, we propose several nonlinear GMM-based transformation functions in an attempt to deal with the over-smoothing effect of linear transformation. In order to obtain high-quality modifications of speech signals our VC system is implemented using the Harmonic plus Noise Model (HNM)analysis/synthesis framework. Experimental results are reported on the English corpus, MOCHA-TlMlT.

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