• 제목/요약/키워드: Random measure.

검색결과 474건 처리시간 0.033초

Statistical Approach to Noisy Band Removal for Enhancement of HIRIS Image Classification

  • Huan, Nguyen Van;Kim, Hak-Il
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 춘계학술대회 논문집
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    • pp.195-200
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    • 2008
  • The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.

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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.

A PARTIAL ORDERING OF WEAK POSITIVE QUADRANT DEPENDENCE

  • Kim, Tae-Sung;Lee, Young-Ro
    • 대한수학회논문집
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    • 제11권4호
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    • pp.1105-1116
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    • 1996
  • A partial ordering is developed among weakly positive quadrant dependent (WPQD) bivariate random vectors. This permits us to measure the degree of WPQD-ness and to compare pairs of WPQD random vectors. Some properties and closures under certain statistical operations are derived. An application is made to measures of dependence such as Kendall's $\tau$ and Spearman's $\rho$.

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Minimum Variance Unbiased Estimation for the Maximum Entropy of the Transformed Inverse Gaussian Random Variable by Y=X-1/2

  • Choi, Byung-Jin
    • Communications for Statistical Applications and Methods
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    • 제13권3호
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    • pp.657-667
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    • 2006
  • The concept of entropy, introduced in communication theory by Shannon (1948) as a measure of uncertainty, is of prime interest in information-theoretic statistics. This paper considers the minimum variance unbiased estimation for the maximum entropy of the transformed inverse Gaussian random variable by $Y=X^{-1/2}$. The properties of the derived UMVU estimator is investigated.

센서 네트워크에서 멀티패스 라우팅 알고리즘의 시뮬레이션 (The Simulation of a Multipath Routing Algorithm in Sensor Networks)

  • 정원도;김기형;손영호
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 2005년도 춘계학술대회 논문집
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    • pp.144-148
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    • 2005
  • The sensor network consists of sensor nodes which communicate wirelessly. It requires energy-efficient routing protocols. We measure requirements in routing protocols by using simulation techniques. In this paper, we propose a random routing algorithm and evaluate it by simulation.

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A PARTIAL ORDERING OF CONDITIONALLY POSITIVE QUADRANT DEPENDENCE

  • Baek, Jong-Il;Choi, Jeong-Yeol;Park, Chun-Ho
    • 대한수학회논문집
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    • 제16권2호
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    • pp.297-308
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    • 2001
  • A partial ordering is developed here among conditionally positive quadrant dependent (CPQD) bivariate random vectors. This permits us to measure the degree of CPQD-ness and to compare pairs of CPQD random vectors. Some properties and closure under certain statistical operations are derived.

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랜덤대치 기반 프라이버시 보호 기법의 효율적인 구현 및 안전성 분석 (Efficient Implementation and Security Analysis of Privacy-Preserving Technique based on Random Substitutions)

  • 안아론;강주성;홍도원
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2007년도 추계학술발표대회
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    • pp.1131-1134
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    • 2007
  • 본 논문에서는 랜덤대치(random substitution) 기법에 대하여 심도 있는 분석을 실시한다. 랜덤대치 기법의 효율적인 구현을 위하여 데이터 재구축(reconstruction) 과정에서 필요로 하는 역행렬을 구하는 공식을 제시한다. 또한, 랜덤대치에 사용되는 다양한 파라미터들의 의미를 실험적으로 밝혀내며, 정확도와 프라이버시를 합리적으로 측정할 수 있는 새로운 측도(measure)들을 제안한다.

입력 도메인 확장을 이용한 반복 분할 기반의 적응적 랜덤 테스팅 기법 (Adaptive Random Testing through Iterative Partitioning with Enlarged Input Domain)

  • 신승훈;박승규
    • 정보처리학회논문지D
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    • 제15D권4호
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    • pp.531-540
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    • 2008
  • 적응적 랜덤 테스팅 (Adaptive Random Testing, ART)은 입력 도메인 내에 테스트 케이스를 넓고 고르게 분산시키는 방법을 통해 입력 도메인 내에 존재하는 오류 패턴을 순수 랜덤 테스팅 (Random Testing, RT)보다 효율적으로 찾아내기 위한 테스트 케이스 선택 기법이다. 테스트 케이스 선택에 많은 연산량을 필요로 하는 초기 ART 기법인 거리 기반 ART (Distance-based ART, D-ART)와 제한 영역 기반 ART (Restricted Random Testing, RRT)의 개선을 위해 입력 도메인을 반복 분할하는 기법들이 제안되었고, 이 기법들은 낮은 연산량 및 성능 향상등의 효과를 가져왔다. 하지만, 입력 도메인 반복 분할 기반 기법에서도 기존 ART 기법에서 나타나는 테스트 케이스 분포 불균일 문제가 존재하고, 이는 기법의 확장성에 장애 요소로 작용한다. 따라서 본 논문에서는 반복 분할 기반 기법에서 나타나는 테스트 케이스 분포의 특성을 파악하고, 이를 적정 수준으로 제어하기 위한 입력 도메인 확장 정책을 제안하였으며, 실험을 통해 2차원 입력 도메인에서 3%, 3차원 입력 도메인에서 10% 수준의 성능 향상을 확인하였다.

실제 환경에 최적화된 MIFARE Classic 공격 절차 (Optimal MIFARE Classic Attack Flow on Actual Environment)

  • 안현진;이예림;이수진;한동국
    • 전기학회논문지
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    • 제65권12호
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    • pp.2240-2250
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    • 2016
  • MIFARE Classic is the most popular contactless smart card, which is primarily used in the management of access control and public transport payment systems. It has several security features such as the proprietary stream cipher Crypto 1, a challenge-response mutual authentication protocol, and a random number generator. Unfortunately, multiple studies have reported structural flaws in its security features. Furthermore, various attack methods that target genuine MIFARE Classic cards or readers have been proposed to crack the card. From a practical perspective, these attacks can be partitioned according to the attacker's ability. However, this measure is insufficient to determine the optimal attack flow due to the refined random number generator. Most card-only attack methods assume a predicted or fixed random number, whereas several commercial cards use unpredictable and unfixable random numbers. In this paper, we propose optimal MIFARE Classic attack procedures with regards to the type of random number generator, as well as an adversary's ability. In addition, we show actual attack results from our portable experimental setup, which is comprised of a commercially developed attack device, a smartphone, and our own application retrieving secret data and sector key.

A GENERALIZATION OF THE INTRACLASS CORRELATION IN CLUSTER SAMPLING

  • KIM KYU-SEONG
    • Journal of the Korean Statistical Society
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    • 제34권3호
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    • pp.185-195
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    • 2005
  • This article is concerned with the intraclass correlation in survey sampling. From a design-based viewpoint the intraclass correlation is generalized to a finite population with unequal sized clusters. Under simple random cluster sampling the intraclass correlation is given in an explicit form, which is a generalization of the usual one. The range of it is found and the design effect is expressed by means of it. An example is given to compare the intraclass correlation with the homogeneity measure numerically, which shows that two measures are not the same except some limited cases.