• 제목/요약/키워드: Spectral Data

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순환 근사 과결정 ARMA 스펙트럼 추정 (Recursive approximate overdetermined ARMA spectral estimation)

  • 이철희;이석원;양흥석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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    • pp.446-450
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    • 1987
  • In this paper, overdetermined method is used for high resolution spectral estimation in case of short data record length. To reduce the computational effort and to obtain recursive form of estimation algorithm, we modify data matrix to have near-Toeplitz structure. Then, new recursive algorithm is derived in the form of fast Kalman algorithm. Two stage procedure is used for the estimation of ARMA parameters. First AR parameters are estimated by using overdetermined modified Yule-walker equation, and then MA parameters are implicitly estimated by estimating numerator spectral coefficients(NS).

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Simultaneous Confidence Regions for Spatial Autoregressive Spectral Densities

  • Ha, Eun-Ho
    • Journal of the Korean Data and Information Science Society
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    • 제10권2호
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    • pp.397-404
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    • 1999
  • For two-dimensional causal spatial autoregressive processes, we propose and illustrate a method for determining asymptotic simultaneous confidence regions using Yule-Walker, unbiased Yule-Walker and least squres estimators. The spectral density for first-order spatial autoregressive model are looked at in more detail. Finite sample properties based on simulation study we also presented.

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발화방식에 따른 미국인 남성 영어모음의 스펙트럼 특성과 포먼트 대역 (Spectral Characteristics and Formant Bandwidths of English Vowels by American Males with Different Speaking Styles)

  • 양병곤
    • 말소리와 음성과학
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    • 제6권4호
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    • pp.91-99
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    • 2014
  • Speaking styles tend to have an influence on spectral characteristics of produced speech. There are not many studies on the spectral characteristics of speech because of complicated processing of too much spectral data. The purpose of this study was to examine spectral characteristics and formant bandwidths of English vowels produced by nine American males with different speaking styles: clear or conversational styles; high- or low-pitched voices. Praat was used to collect pitch-corrected long-term averaged spectra and bandwidths of the first two formants of eleven vowels in the speaking styles. Results showed that the spectral characteristics of the vowels varied systematically according to the speaking styles. The clear speech showed higher spectral energy of the vowels than that of the conversational speech while the high-pitched voice did the same over the low-pitched voice. In addition, front and back vowel groups showed different spectral characteristics. Secondly, there was no statistically significant difference between B1 and B2 in the speaking styles. B1 was generally lower than B2 when reflecting the source spectrum and radiation effect. However, there was a statistically significant difference in B2 between the front and back vowel groups. The author concluded that spectral characteristics reflect speaking styles systematically while bandwidths measured at a few formant frequency points do not reveal style differences properly. Further studies would be desirable to examine how people would evaluate different sets of synthetic vowels with spectral characteristics or with bandwidths modified.

A Max-Flow-Based Similarity Measure for Spectral Clustering

  • Cao, Jiangzhong;Chen, Pei;Zheng, Yun;Dai, Qingyun
    • ETRI Journal
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    • 제35권2호
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    • pp.311-320
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    • 2013
  • In most spectral clustering approaches, the Gaussian kernel-based similarity measure is used to construct the affinity matrix. However, such a similarity measure does not work well on a dataset with a nonlinear and elongated structure. In this paper, we present a new similarity measure to deal with the nonlinearity issue. The maximum flow between data points is computed as the new similarity, which can satisfy the requirement for similarity in the clustering method. Additionally, the new similarity carries the global and local relations between data. We apply it to spectral clustering and compare the proposed similarity measure with other state-of-the-art methods on both synthetic and real-world data. The experiment results show the superiority of the new similarity: 1) The max-flow-based similarity measure can significantly improve the performance of spectral clustering; 2) It is robust and not sensitive to the parameters.

변동풍속의 파워 스펙트럴 밀도에 관한 평가 (Estimation on the Power Spectral Densities of Daily Instantaneous Maximum Fluctuation Wind Velocity)

  • 오종섭
    • 한국방재안전학회논문집
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    • 제10권2호
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    • pp.21-28
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    • 2017
  • 시공간적으로 불규칙하게 작용하는 변동 풍속 난류의 자료는 풍공학적으로 돌풍계수 평균풍속 변동 풍하중등의 계산에서 요구되지만, 내풍 및 사용성에 따른 동적응답의 평가에서는 변동 풍속의 파워 스펙트럴 밀도함수가 요구된다. 본 논문에서는 1987-2016.12.1일까지의 일순간최대풍속 자료를 확률과정으로 가정했고, 이 실측된 자료와 확률이론을 근거로 평균류방향 파워 스펙트럴 밀도 함수에 대한 기초적 자료를 얻고자 대표지점(6개 지점)을 선정했다. 선정된 각 지점에 대한 일순간최대풍속자료는 기상청으로부터 획득했다. 해석결과 본 논문에서 평가된 스펙트럼 모델은 저진동수 영역에서는 Solari, 고진동수 영역에서는 von Karman의 모델과 근접한 현상을 나타냈다.

주파수 효율적 재전송 기반 원격측정 성능 향상 (Telemetry Performance Enhancement Based on Spectral Efficient Retransmission)

  • 박청운;박효섭
    • 한국항공우주학회지
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    • 제45권5호
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    • pp.429-436
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    • 2017
  • 본 논문은 기존의 시간 지연 데이터를 이용한 원격 측정 방법에서 생기는 무선 채널 비효율성을 증대시키기 위하며 주파수 효율적 재전송 방법을 제시하였다. 제시된 방법은 트리거 기반 메모리를 사용하여 주파수 효율적으로 데이터를 재전송한다. 이는 원격측정데이터를 수신하는 과정에서 다중경로페이딩이나 송신 안테나 패턴에 의해 영향 받는 통신환경 뿐 아니라 원격 측정 데이터를 송신하는 과정에서 이벤트에 의해 송신 환경에서 생기는 오류 데이터를 최소화한다. 비행시험 결과 데이터에서 주파수 효율적 재전송 데이터를 이용하여 원격측정의 성능 향상을 입증한다.

Noisy Band Removal Using Band Correlation in Hyperspectral lmages

  • Huan, Nguyen Van;Kim, Hak-Il
    • 대한원격탐사학회지
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    • 제25권3호
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    • pp.263-270
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    • 2009
  • Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

다중시기 위성영상을 이용한 시화 방조제 내만 식생변화탐지 (Vegetation Change Detection in the Sihwa Embankment using Multi-Temporal Satellite Data)

  • 정종철;서영상;김상욱
    • 한국환경과학회지
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    • 제15권4호
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    • pp.373-378
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    • 2006
  • The western coast of South Korea is famous for its large and broad tidal lands. Nevertheless, land reclamation, which has been conducted on a large scale, such as Sihwa embankment construction project has accelerated coastal environmental changes in the embankment inland. For monitoring of environmental change, vegetation change detecting of the embankment inland were carried out and field survey data compared with Landsat TM, ETM+, IKONOS, and EOC satellite remotely sensed data. In order to utilize multi-temporal remotely sensed images effectively, all data set with pixel size were analyzed by same geometric correction method. To detect the tidal land vegetation change, the spectral characteristics and spatial resolution of Landsat TM and ETM+ images were analyzed by SMA(spectral mixture analysis). We obtained the 78.96% classification accuracy and Kappa index 0.2376 using March 2000 Landsat data. The SMA(spectral mixture analysis) results were considered with comparing of vegetation seasonal change detection method.

A New Method for Hyperspectral Data Classification

  • Dehghani, Hamid.;Ghassemian, Hassan.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.637-639
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    • 2003
  • As the number of spectral bands of high spectral resolution data increases, the capability to detect more detailed classes should also increase, and the classification accuracy should increase as well. Often, it is impossible to access enough training pixels for supervise classification. For this reason, the performance of traditional classification methods isn't useful. In this paper, we propose a new model for classification that operates based on decision fusion. In this classifier, learning is performed at two steps. In first step, only training samples are used and in second step, this classifier utilizes semilabeled samples in addition to original training samples. At the beginning of this method, spectral bands are categorized in several small groups. Information of each group is used as a new source and classified. Each of this primary classifier has special characteristics and discriminates the spectral space particularly. With using of the benefits of all primary classifiers, it is made sure that the results of the fused local decisions are accurate enough. In decision fusion center, some rules are used to determine the final class of pixels. This method is applied to real remote sensing data. Results show classification performance is improved, and this method may solve the limitation of training samples in the high dimensional data and the Hughes phenomenon may be mitigated.

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산림지역의 항공기 탑재 하이퍼스펙트럴 영상에 대한 식생-Endmember와 식생지수의 상관 분석 (Correlation Analysis with Vegetation Indices and Vegetation-Endmembers From Airborne Hyperspectral Data in Forest Area)

  • 김태우;위광재;서용철
    • 한국지리정보학회지
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    • 제15권3호
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    • pp.52-65
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    • 2012
  • 작물과 산림을 포함한 식생에 대한 순1차 생산(net primary production, NPP)와 총1차 생산(gross primary production, GPP)은 바이오매스와 식생의 탄소저장과 밀접한 관련이 있으며, 원격탐사를 이용해 바이오매스를 추정하는 많은 노력이 이루어지고 있다. 바이오매스는 광합성에 매우 중요한 요소인 클로로필(엽록소)의 총 함유량으로 추정할 수 있는데, 클로로필을 추정하기 위해서 다양한 식생지수들이 개발되었다. 식생지수들은 개발에 사용된 식생의 종류와 원격탐사 데이터에 따라 조금씩 차이를 가지고 있다. 하이퍼스펙트럴 영상은 다중분광 영상에 비하여 세분화된 각 파장대마다 물질에 따른 반사 및 흡수 특성이 다르기 때문에, 기존의 식생지수를 그대로 사용하기에 무리가 따른다. 본 연구는 항공기 탑재 하이퍼스펙트럴 영상을 이용하여 산림에 대한 바이오매스 추정을 위한 매개변수로 활용되는 적합한 식생지수는 무엇인지 평가하는 것을 목적으로 한다. 이를 위해 하이퍼스펙트럴 영상의 밴드 특성을 고려하여 다수의 식생지수 산출식 중 9개를 선정하고, SMA(spectral mixture analysis)를 통하여 대상지역의 산림을 대표하는 3개의 endmember를 추출하였다. 9개의 식생지수와 추출된 endmembers의 상관관계를 분석하였다. 상관분석 결과는 산림이 분포된 지역에서 Pearson 상관계수는 MTVI1과 TVI가 0.877의 상관계수를 가졌으며, 식생이 적고 토양의 분포가 확연한 지역에서는 MCARI가 0.9061로 매우 높은 상관계수를 보였다. 전반적으로 MTVI1과 TVI이 0.757의 동일한 상관계수를 가지며 식생에 대한 3개의 endmember를 가장 잘 설명하는 것으로 나타났다.