• 제목/요약/키워드: spectral function

검색결과 822건 처리시간 0.046초

REMARKS ON SPECTRAL PROPERTIES OF p-HYPONORMAL AND LOG-HYPONORMAL OPERATORS

  • DUGGAL BHAGWATI P.;JEON, IN-HO
    • 대한수학회보
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    • 제42권3호
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    • pp.543-554
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    • 2005
  • In this paper it is proved that for p-hyponormal or log-hyponormal operator A there exist an associated hyponormal operator T, a quasi-affinity X and an injection operator Y such that TX = XA and AY = YT. The operator A and T have the same spectral picture. We apply these results to give brief proofs of some well known spectral properties of p-hyponormal and log­hyponormal operators, amongst them that the spectrum is a con­tinuous function on these classes of operators.

설계응답스펙트럼에 부합하는 목표 PSD함수의 작성 (Generation of Target PSD Function Compatible with Design Response Spectrum)

  • 이상훈;최동호
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2006년도 학술발표회 논문집
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    • pp.637-644
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    • 2006
  • Acceleration time history used in the seismic analysis of nuclear porter plant structure should envelop a target power spectral density (PSD) function in addition to design response spectrum. Current regulation guide defines the target PSD function only for the U.S. URC RG 1.60 Design Response Spectrum. This paper proposes a technical scheme to obtain the target PSD function compatible with generally defined design response spectrum. The scheme includes the methodology for design-spectrum compatible motion history in order to minimize the variation of the derived target PSD function. The PSD calculation procedure follows simple and practical methods allowed within regulation. Effectiveness of the proposed scheme is identified through an example problem. The design response spectrum In the example is based on U.S. NRC RG 1.60 but amplifies the spectral acceleration amplitudes above 9Hz. The target PSD function with little variation can be constructed with the reduced time history ensemble.

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ON THE UNIFORM CONVERGENCE OF SPECTRAL EXPANSIONS FOR A SPECTRAL PROBLEM WITH A BOUNDARY CONDITION RATIONALLY DEPENDING ON THE EIGENPARAMETER

  • Goktas, Sertac;Kerimov, Nazim B.;Maris, Emir A.
    • 대한수학회지
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    • 제54권4호
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    • pp.1175-1187
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    • 2017
  • The spectral problem $$-y^{{\prime}{\prime}}+q(x)y={\lambda}y,\;0 < x < 1, \atop y(0)cos{\beta}=y^{\prime}(0)sin{\beta},\;0{\leq}{\beta}<{\pi};\;{\frac{y^{\prime}(1)}{y(1)}}=h({\lambda})$$ is considered, where ${\lambda}$ is a spectral parameter, q(x) is real-valued continuous function on [0, 1] and $$h({\lambda})=a{\lambda}+b-\sum\limits_{k=1}^{N}{\frac{b_k}{{\lambda}-c_k}},$$ with the real coefficients and $a{\geq}0$, $b_k$ > 0, $c_1$ < $c_2$ < ${\cdots}$ < $c_N$, $N{\geq}0$. The sharpened asymptotic formulae for eigenvalues and eigenfunctions of above-mentioned spectral problem are obtained and the uniform convergence of the spectral expansions of the continuous functions in terms of eigenfunctions are presented.

Robust Similarity Measure for Spectral Clustering Based on Shared Neighbors

  • Ye, Xiucai;Sakurai, Tetsuya
    • ETRI Journal
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    • 제38권3호
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    • pp.540-550
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    • 2016
  • Spectral clustering is a powerful tool for exploratory data analysis. Many existing spectral clustering algorithms typically measure the similarity by using a Gaussian kernel function or an undirected k-nearest neighbor (kNN) graph, which cannot reveal the real clusters when the data are not well separated. In this paper, to improve the spectral clustering, we consider a robust similarity measure based on the shared nearest neighbors in a directed kNN graph. We propose two novel algorithms for spectral clustering: one based on the number of shared nearest neighbors, and one based on their closeness. The proposed algorithms are able to explore the underlying similarity relationships between data points, and are robust to datasets that are not well separated. Moreover, the proposed algorithms have only one parameter, k. We evaluated the proposed algorithms using synthetic and real-world datasets. The experimental results demonstrate that the proposed algorithms not only achieve a good level of performance, they also outperform the traditional spectral clustering algorithms.

Spectral density functions of wind pressures on various low building roof geometries

  • Kumar, K. Suresh;Stathopoulos, T.
    • Wind and Structures
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    • 제1권3호
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    • pp.203-223
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    • 1998
  • This paper describes in detail the features of an extensive study on Spectral Density Functions (SDF's) of wind pressures acting on several low building roof geometries carried out in a boundary layer wind tunnel. Various spectral characteristics of wind pressures on roofs with emphasis on derivation of suitable analytical representation of spectra and determination of characteristic spectral shapes are shown. Standard spectral shapes associated with various zones of each roof and their parameters are provided. The established spectral parameters can be used to generate synthetic spectra adequate for the simulation of wind pressure fluctuations on building surfaces in a generic fashion.

Spectral clustering based on the local similarity measure of shared neighbors

  • Cao, Zongqi;Chen, Hongjia;Wang, Xiang
    • ETRI Journal
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    • 제44권5호
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    • pp.769-779
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    • 2022
  • Spectral clustering has become a typical and efficient clustering method used in a variety of applications. The critical step of spectral clustering is the similarity measurement, which largely determines the performance of the spectral clustering method. In this paper, we propose a novel spectral clustering algorithm based on the local similarity measure of shared neighbors. This similarity measurement exploits the local density information between data points based on the weight of the shared neighbors in a directed k-nearest neighbor graph with only one parameter k, that is, the number of nearest neighbors. Numerical experiments on synthetic and real-world datasets demonstrate that our proposed algorithm outperforms other existing spectral clustering algorithms in terms of the clustering performance measured via the normalized mutual information, clustering accuracy, and F-measure. As an example, the proposed method can provide an improvement of 15.82% in the clustering performance for the Soybean dataset.

옷가지와 안경 착용에 따른 머리전달함수의 스펙트럼 왜곡 (Spectral Distortion of Head-Related Transfer Function Due to Wearing Clothes and Glasses)

  • 조현;황성목;이윤재;박영진;박윤식
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2009년도 춘계학술대회 논문집
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    • pp.103-107
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    • 2009
  • Because individual HRTFs (Head-Related Transfer Functions) vary from a person to a person, a HRTF database has been measured by researchers to investigate the inter-subject variation, and to generate high fidelity virtual sound image. Individual HRTFs not only vary between subjects but also vary due to wearing clothes and glasses in daily life. However, influence of different dressing condition on the measured HRTF was not sufficiently investigated. To quantify the effect of wearing clothes and glasses, dummy's HRTF is measured in an anechoic chamber with various dressing condition, and is evaluated in the sense of spectral distortion. HRTFs are measured both in the median plane and in the horizontal plane. In the median plane, under 6kHz, effect of different wearing clothes and glasses is negligible. Over 6kHz, however, effect of clothing distorts HRTF about 6dB in the sense of spectral distortion. Moreover, at high frequencies, effect of glasses is no longer negligible. In the horizontal plane, at some azimuths, even additional light cloth over the dummy can change the spectrum of HRTF (6dB spectral distortion) especially when sound source is at contralateral positions. Therefore, HRTF measurement with different wearing conditions can broaden the capability of HRTF customization whose technique utilizes a HRTF database.

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Correlations of Rice Grain Yields to Radiometric Estimates of Canopy Biomass as a Function of Growth Stage, : Hand-Held Radiometric Measurements of Two of the Thematic Mapper's Spectral Bands Indicate that the Forecasting of Rice Grain Yields is Feasible at Early to Mid Canopy Development Stages

  • Yang, Young-Kyu;Miller, Lee-D.
    • 대한원격탐사학회지
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    • 제1권1호
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    • pp.63-87
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    • 1985
  • Considerable experience has been reported on the use of spectral data to measure the canopy biomass of dryland grain crops and the use of these estimates to forecast subsequent grain yield. These basic procedures were retested to assess the use of the general process to forecasting grain yield for paddy rice. The use of the ratio of a multiband radiometer simulation of Thematic Mapper band 4(.76 to .90 .mu.m) divided by band 3 (.63 to .69 .mu.m) was tested to estimate the canopy biomass of paddy rice as a function of the stage of development of the rice. The correlation was found to be greatest (R = .94) at panicle differentiation about midway through the development cycle of the rice canopy. The use of this ratio of two spectral bands as a surrogate for canopy biomass was then tested for its correlation against final grain yield. These spectral estimates of canopy biomass produced the highest correlations with final grain yield (R = .87) when measured at the canopy development stages of panicle differentiation and heading. The impact of varying the amounts of supplemental nitrogen on the use of spectral measuremants of canopy biomass to estimate grain yield was also determined. The effect of the development of a significant amount of weed biomass in the rice canopy was also clearly detected.

An analysis method of reflectance spectra of strongly correlated electron systems

  • Hwang, Jungseek
    • 한국초전도ㆍ저온공학회논문지
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    • 제15권1호
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    • pp.14-18
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    • 2013
  • We introduce a generic method to analyze optical 17reflectance spectra of strongly correlated electron systems including high-temperature superconductors by using an extended Drude model and Allen's approach. We explain the process step by step from reflectance through the optical conductivity and the scattering rate to the bosonic spectral function. Through the process we are able to get important information on the interactions between charge carriers from measured optical conductivity of the strongly correlated electron systems including copper oxide and iron pnitide high temperature superconductors.

Automatic Cross-calibration of Multispectral Imagery with Airborne Hyperspectral Imagery Using Spectral Mixture Analysis

  • Yeji, Kim;Jaewan, Choi;Anjin, Chang;Yongil, Kim
    • 한국측량학회지
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    • 제33권3호
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    • pp.211-218
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    • 2015
  • The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.