• Title/Summary/Keyword: cumulative distribution function (CDF)

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CHARACTERIZATIONS BASED ON THE INDEPENDENCE OF THE EXPONENTIAL AND PARETO DISTRIBUTIONS BY RECORD VALUES

  • LEE MIN-YOUNG;CHANG SE-KYUNG
    • Journal of applied mathematics & informatics
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    • v.18 no.1_2
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    • pp.497-503
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    • 2005
  • This paper presents characterizations on the independence of the exponential and Pareto distributions by record values. Let ${X_{n},\;n {\ge1}$ be a sequence of independent and identically distributed(i.i.d) random variables with a continuous cumulative distribution function(cdf) F(x) and probability density function(pdf) f(x). $Let{\;}Y_{n} = max{X_1, X_2, \ldots, X_n}$ for n \ge 1. We say $X_{j}$ is an upper record value of ${X_{n},{\;}n\ge 1}, if Y_{j} > Y_{j-1}, j > 1$. The indices at which the upper record values occur are given by the record times {u(n)}, n \ge 1, where u(n) = $min{j|j > u(n-1), X_{j} > X_{u(n-1)}, n \ge 2}$ and u(l) = 1. Then F(x) = $1 - e^{-\frac{x}{a}}$, x > 0, ${\sigma} > 0$ if and only if $\frac {X_u(_n)}{X_u(_{n+1})} and X_u(_{n+1}), n \ge 1$, are independent. Also F(x) = $1 - x^{-\theta}, x > 1, {\theta} > 0$ if and only if $\frac {X_u(_{n+1})}{X_u(_n)}{\;}and{\;} X_{u(n)},{\;} n {\ge} 1$, are independent.

Radar Pulse Clustering using Kernel Density Window (커널 밀도 윈도우를 이용한 레이더 펄스 클러스터링)

  • Lee, Dong-Weon;Han, Jin-Woo;Lee, Won-Don
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.973-974
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    • 2008
  • As radar signal environments become denser and more complex, the capability of high-speed and accurate signal analysis is required for ES(Electronic warfare Support) system to identify individual radar signals at real-time. In this paper, we propose the new novel clustering algorithm of radar pulses to alleviate the load of signal analysis process and support reliable analysis. The proposed algorithm uses KDE(Kernel Density Estimation) and its CDF(Cumulative Distribution Function) to compose clusters considering the distribution characteristics of pulses. Simulation results show the good performance of the proposed clustering algorithm in clustering and classifying the emitters.

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Measure and Analysis of Open-Close Frequency of Mouth and Eyes for Sleepiness Decision (졸음 판단을 위한 눈과 입의 개폐 빈도수 측정 및 분석)

  • Sung, Jae-Kyung;Choi, In-Ho;Park, Sang-Min;Kim, Yong-Guk
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.89-97
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    • 2014
  • In this paper, we propose real-time program that measure open-close frequency of mouth and eyes to detect drowsiness of a driver. This program detects a face to the CCD camera image using OpenCV library. Then that extracts each area using CDF for eye detection and Active Contour for mouth detection based on detected face. This system measures each frequency of Open-Close using extracted area data of eyes and mouth. We propose foundation technique how to perform sleepiness decision of users based on measurement data.

Comparison of Statistical Models for Analysis of Fatigue Life of Cable (케이블 피로 수명 해석 통계 모델 비교)

  • Suh, Jeong-In;Yoo, Sung-Won
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.7 no.4
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    • pp.129-137
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    • 2003
  • The cable in the cable-supported structures is long, therefore it can be reasonable to apply the different models, compared with those used for general steel elements. This paper compares the statistical models with existing cable fatigue data, after deriving the cdf(cumulative distibution function) with modifying the log-normal distribution, the existing extremal distributions so as to include length effect. The paper presents the appropriate model for analyzing and assessing the fatigue behavior of cable which is being used for actual structures.

Bias Correction for GCM Long-term Prediction using Nonstationary Quantile Mapping (비정상성 분위사상법을 이용한 GCM 장기예측 편차보정)

  • Moon, Soojin;Kim, Jungjoong;Kang, Boosik
    • Journal of Korea Water Resources Association
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    • v.46 no.8
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    • pp.833-842
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    • 2013
  • The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

Threshold Estimation of Generalized Pareto Distribution Based on Akaike Information Criterion for Accurate Reliability Analysis (정확한 신뢰성 해석을 위한 아카이케 정보척도 기반 일반화파레토 분포의 임계점 추정)

  • Kang, Seunghoon;Lim, Woochul;Cho, Su-Gil;Park, Sanghyun;Lee, Minuk;Choi, Jong-Su;Hong, Sup;Lee, Tae Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.39 no.2
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    • pp.163-168
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    • 2015
  • In order to perform estimations with high reliability, it is necessary to deal with the tail part of the cumulative distribution function (CDF) in greater detail compared to an overall CDF. The use of a generalized Pareto distribution (GPD) to model the tail part of a CDF is receiving more research attention with the goal of performing estimations with high reliability. Current studies on GPDs focus on ways to determine the appropriate number of sample points and their parameters. However, even if a proper estimation is made, it can be inaccurate as a result of an incorrect threshold value. Therefore, in this paper, a GPD based on the Akaike information criterion (AIC) is proposed to improve the accuracy of the tail model. The proposed method determines an accurate threshold value using the AIC with the overall samples before estimating the GPD over the threshold. To validate the accuracy of the method, its reliability is compared with that obtained using a general GPD model with an empirical CDF.

An Adaptive Histogram Redistribution Algorithm Based on Area Ratio of Sub-Histogram for Contrast Enhancement (명암비 향상을 위한 서브-히스토그램 면적비 기반의 적응형 히스토그램 재분배 알고리즘)

  • Park, Dong-Min;Choi, Myung-Ruyl
    • The KIPS Transactions:PartB
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    • v.16B no.4
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    • pp.263-270
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    • 2009
  • Histogram Equalization (HE) is a very popular technique for enhancing the contrast of an image. HE stretches the dynamic range of an image using the cumulative distribution function of a given input image, therefore improving its contrast. However, HE has a well-known problem : when HE is applied for the contrast enhancement, there is a significant change in brightness. To resolve this problem, we propose An Adaptive Contrast Enhancement Algorithm using Subhistogram Area-Ratioed Histogram Redistribution, a new method that helps reduce excessive contrast enhancement. This proposed algorithm redistributes the dynamic range of an input image using its mean luminance value and the ratio of sub-histogram area. Experimental results show that by this redistribution, the significant change in brightness is reduced effectively and the output image is able to preserve the naturalness of an original image even if it has a poor histogram distribution.

Performance Analysis of Distributed Antenna Systems with Antenna Selection over MIMO Rayleigh Fading Channel

  • Yu, Xiangbin;Tan, Wenting;Wang, Ying;Liu, Xiaoshuai;Rui, Yun;Chen, Ming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.3016-3033
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    • 2014
  • The downlink performance of distributed antenna systems (DAS) with antennas selection is investigated in Rayleigh fading multicell environment, and the corresponding system capacity and bit error rate (BER) analysis are presented. Based on the moment generating function, the probability density function (PDF) and cumulative distribution function (CDF) of the effective signal to interference plus noise ratio (SINR) of the system are first derived, respectively. Then, with the available CDF and PDF, the accurate closed-form expressions of average channel capacity and average BER are further derived for exact performance evaluation. To simplify the expression, a simple closed-form approximate expression of average channel capacity is obtained by means of Taylor series expansion, with the performance results close to the accurate expression. Besides, the system outage capacity is analyzed, and an accurate closed-form expression of outage capacity probability is derived. These theoretical expressions can provide good performance evaluation for DAS downlink. It can be shown by simulation that the theoretical analysis and simulation are consistent, and DAS with antenna selection outperforms that with conventional blanket transmission. Moreover, the system performance can be effectively improved as the number of receive antennas increases.

Characteristics Analysis of the Time Selective Multipath Fading Channel Model for Mobile Communication (이동 통신을 위한 시간선택성 다중경로 페이딩 채널 모델의 특성 평가)

  • 박수진;고석준;이경하;최형진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.5A
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    • pp.836-845
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    • 2001
  • 본 논문에서는 시간 선택성 다중경로 이동 무선 채널을 다양한 방법으로 모델링 하고 그에 따른 여러 가지 특성평가를 제시하였다. 모델링 방법에는 Jakes 방식과 시간 영역에서 독립적인 두 개의 가우시안 잡음 발생기와 정형필터(shaping filter)를 사용하는 방식 및 주파수 영역에서 필터링 하는 방식이 있다. 이 세 가지 모델링 방법의 성능을 진폭의 자기상관함수, 상호상관함수, 누적분포함수(Cumulative Distribution Function), 레벨 교차율(Level Crossing Rate), 평균 페이딩 지속 시간(Average Duration of Fades), 위상차의 확률 밀도, 위상차의 자기상관함수 등의 측면에서 시뮬레이션하고 그 결과치와 이론치 간의 특성 비교를 제시하였다. 특히, 확산 대역 시스템을 고려했을 때 이상적인 채널 추정을 가정한 레이크 수신기에서의 BER 성능을 다중경로 개수에 따라 보임으로써 여러 가지 채널 모델링 중에서 주파수 영역에서 필터링 하는 방식이 이동 무선 채널을 모델링 하는데 있어 가장 적합하다는 것을 보였다. 마지막으로 비대칭 도플러(Doppler) 스펙트럼을 모델링 하는 것도 주파수 영역에서 필터링 하는 방식이 편리하다.

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An Improved Block-matching Algorithm Based on Motion Similarity of Adjacent Macro-blocks (인접 매크로블록간 움직임유사도 기반 개선된 블록매칭 알고리즘)

  • Ryu, Tae-kyung;Jeong, Yong-jae;Moon, Kwang-seok;Kim, Jong-nam
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.663-667
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    • 2009
  • 본 논문에서는 인접블록간의 움직임 유사도를 이용하여 불필요한 후보블록을 보다 빠르게 제거하는 PDE기반의 고속 블록매칭 알고리즘을 제안한다. 제안한 방법은 기존의 방법보다 불필요한 계수를 효율적으로 제거하기 위하여 인접 블록간의 영상의 유사성에 기초하여 인접한 네개의 매크로블록 가운데 최대 복잡도를 가지는 서브블록의 누적된 비율(cumulative distribution function-CDF)을 사용하고 서브블록별 복잡도가 집중되지 않도록 하기위하여 normalized 기반 매칭스캔 방법을 사용하여 효율적으로 계산량을 줄였다. 제안한 알고리즘은 화질의 저하 없이 기존의 PDE 알고리즘에 비해 60% 이상의 계산량을 줄였으며, MPEG-2 및 MPEG-4 AVC를 이용하는 비디오 압축 응용분야에 유용하게 사용될 수 있을 것이다.

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