• 제목/요약/키워드: Probability Density Distribution and function

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Dual-Hop Amplify-and-Forward Multi-Relay Maximum Ratio Transmission

  • Erdogan, Eylem;Gucluoglu, Tansal
    • Journal of Communications and Networks
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    • 제18권1호
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    • pp.19-26
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    • 2016
  • In this paper, the performance of dual-hop multi-relay maximum ratio transmission (MRT) over Rayleigh flat fading channels is studied with both conventional (all relays participate the transmission) and opportunistic (best relay is selected to maximize the received signal-to-noise ratio (SNR)) relaying. Performance analysis starts with the derivation of the probability density function, cumulative distribution function and moment generating function of the SNR. Then, both approximate and asymptotic expressions of symbol error rate (SER) and outage probability are derived for arbitrary numbers of antennas and relays. With the help of asymptotic SER and outage probability, diversity and array gains are obtained. In addition, impact of imperfect channel estimations is investigated and optimum power allocation factors for source and relay are calculated. Our analytical findings are validated by numerical examples which indicate that multi-relay MRT can be a low complexity and reliable option in cooperative networks.

INTRODUCTION OF THREE FUNCTIONAL MODELS MATCHED TO THE STOCHASTIC RESPONSE EVALUATION OF ACOUSTIC ENVIRONMENTAL SYSTEM AND ITS APPLICATION TO A SOUND INSULATION SYSTEM

  • Ohta, Mitsuo;Fujita, Yoshifumi
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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    • pp.686-691
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    • 1994
  • For evaluating the response fluctuation of the actual environmental acoustic system excited by arbitrary random inputs, it is important to predict a whole probability distribution form closely connected with evaluation indexes Lx, Leq and so on. In this paper, a new type evaluation method is proposed by introducing three functional models matched to the prediction of the response probability distribution from a problem-oriented viewpoint. Because of the positive variable of the sound intensity, the response probability density function can be reasonably expressed theoretically by a statistical Laguerre expansion series form. The relationship between input and output is described by the regression relationship between the distribution parameters(containing expansion coefficients of this expression) and the stochastic input. These regression functions are expressed in terms of the orthogonal series expansion and their parameters are determined based on the least-squares error criterion and the measure of statistical independency.

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원형 다이아몬드 톱의 세그먼트 표면에서의 다이아몬드 입자 분포의 확률적인 해석 (Stochastic Analysis of the Diamond Particle Distribution on the Surface of Circular Diamond Saw Blade)

  • 이현우;변서봉;정기정;김용석
    • 한국분말재료학회지
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    • 제10권3호
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    • pp.201-208
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    • 2003
  • Distributions of diamond particles protruding on the surface of worn diamond segments in circular saw has been investigated. Scanning electron microscope was used to examine the worn ,surface and radial saw blade wear and grinding ratio was measured. The number of protruded diamond particle was approximately 50% of the total number of particles, and that was independent of diamond particle concentration and table speed. It was also noted that the inter-particle distance did not follow a symmetric function like Gaussian distribution function, instead it fitted well with a probability density function based on gamma function. The distribution of inter-particle spacing, therefore, was analyzed using a gamma function model.

Bayesian estimation for Rayleigh models

  • Oh, Ji Eun;Song, Joon Jin;Sohn, Joong Kweon
    • Journal of the Korean Data and Information Science Society
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    • 제28권4호
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    • pp.875-888
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    • 2017
  • The Rayleigh distribution has been commonly used in life time testing studies of the probability of surviving until mission time. We focus on a reliability function of the Rayleigh distribution and deal with prior distribution on R(t). This paper is an effort to obtain Bayes estimators of rayleigh distribution with three different prior distribution on the reliability function; a noninformative prior, uniform prior and inverse gamma prior. We have found the Bayes estimator and predictive density function of a future observation y with each prior distribution. We compare the performance of the Bayes estimators under different sample size and in simulation study. We also derive the most plausible region, prediction intervals for a future observation.

확률밀도함수와 KOMPSAT-3A를 활용한 산불피해강도 분류 (Forest Fire Severity Classification Using Probability Density Function and KOMPSAT-3A)

  • 이승민;정종철
    • 대한원격탐사학회지
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    • 제35권6_4호
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    • pp.1341-1350
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    • 2019
  • 본 연구는 산불 전후 KOMPSAT-3A 영상을 사용하여 산불피해지역을 분석하는 것을 목적으로 한다. KOMPSAT 시리즈 중 KOMPSAT-3A는 적외선 및 고해상도의 멀티 스펙트럼 밴드를 가진 VHR위성이다. 하지만, KOMPSAT-3A를 활용하여 산불피해강도를 분류하는 연구는 부족한 실정이다. 따라서 본 연구에서는 KOMPSAT-3A의 산불 피해강도를 분류하기 위한 새로운 알고리즘을 제시하는 것을 목표로 한다. 또한, 본 연구에서는 산불 피해지역에 대한 참조자료로 Sentinel-2로 생성한 dNBR을 사용하였다. 본 연구의 연구 지역은 2019년 4월 4일 강릉에서 발생한 산불 피해지역으로 선정하였다. 본 연구에서는 산불피해구간을 산정하기 위한 알고리즘으로 오픈 소스 통계 프로그램인 R software의 확률분포함수를 사용하였다. KOMPSAT-3A에서 산불 피해지역은 산불 전, 후 NDVI의 변화에 따라 생성되었다. 산불피해강도는 분포 함수의 표준 편차를 사용하여 각 등급 크기를 산정하였다. 총 5개 구간에 따른 산불 피해 강도가 효과적으로 분류되었다.

CHARACTERIZATIONS OF BETA DISTRIBUTION OF THE FIRST KIND BY CONDITIONAL EXPECTATIONS OF RECORD VALUES

  • Lee, Min-Young;Chang, Se-Kyung
    • Journal of applied mathematics & informatics
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    • 제13권1_2호
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    • pp.441-446
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    • 2003
  • Let { $X_{n}$ , n $\geq$ 1} be a sequence of independent and identically distributed random variables with a common continuous distribution function F(x) and probability density function f(x). Let $Y_{n}$ = max{ $X_1$, $X_2$, …, $X_{n}$ } for n $\geq$ 1. We say $X_{j}$ is an upper record value of { $X_{n}$ , n$\geq$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$\geq$1, where u(n) = min{j|j>u(n-1), $X_{j}$ > $X_{u}$ (n-1), n$\geq$2} and u(1) = 1. We call the random variable X $\in$ Beta (1, c) if the corresponding probability cumulative function F(x) of x is of the form F(x) = 1-(1-x)$^{c}$ , c>0, 0$\leq$x$\leq$1. In this paper, we will give a characterization of the beta distribution of the first kind by considering conditional expectations of record values.s.

한반도 연안 조위편차의 확률밀도함수 (Probability Density Function of the Tidal Residuals in the Korean Coast)

  • 조홍연;강주환
    • 한국해안·해양공학회논문집
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    • 제24권1호
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    • pp.1-9
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    • 2012
  • 조위편차는 최근 기후변화에 의한 영향으로 연안 안전 방재 측면에서 매우 중요한 인자로 부각되고 있다. 태풍강도 등과 더불어 변화가 예상되는 조위편차는 해안구조물의 안전 및 기능검토에 필요한 기준해수면 결정에 기여하는 중요한 인자이다. 우리나라 연안 조위편차의 확률밀도함수는 음 양의 왜도와 정규분포보다 큰 돌도를 가지는 분포로, 정규분포로 근사화하는 방법은 한계가 있기 때문에 본 연구에서는 비모수적 방법인 Kernel 함수를 이용하여 확률밀도함수를 추정 제안하였다. 본 연구에서 제안된 확률밀도함수는 조위편차자료의 분포와 매우 우수한 일치수준을 보이고 있으며, 다양한 극값 추정에도 높은 수준의 정도를 보여주고 있다.

상륙 태풍에 의한 마산만 폭풍해일 변동성 분석 - 1. 극치 모의 태풍 시나리오의 결정 (Variation Analysis of Storm Surges in Masan Bay due to Typhoon Landing-1. Extreme Simulation Typhoon Scenario)

  • Han, Sungdae
    • 한국재난정보학회 논문집
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    • 제11권4호
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    • pp.493-505
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    • 2015
  • 남해안에 상륙한 태풍 자료를 기초로 하여 분석한 결과, 태풍 이동방향의 분포는 Beta 확률밀도함수를 따르며, 태풍 눈에서의 기압저하는 Rayleigh 확률밀도함수를 따르는 것으로 판단되었다. 이를 바탕으로 6개 상륙 지점에 따라 가장 확률적으로 높은 태풍의 진로와 기압저하에 따른 태풍 매미급의 극치 태풍 모의 시나리오를 결정하였다. 모의된 태풍의 상륙지점에 따른 마산만에서의 폭풍해일 변동성이 후속 연구에서 수치 모의될 것이다.

An image enhancement Method for extracting multi-license plate region

  • Yun, Jong-Ho;Choi, Myung-Ryul;Lee, Sang-Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권6호
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    • pp.3188-3207
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    • 2017
  • In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.

On Radar Surveillance in Statistical Perspective for the Classroom

  • Kim, G. Daniel;Kim, Sung-Sook
    • 한국수학교육학회지시리즈D:수학교육연구
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    • 제6권1호
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    • pp.97-106
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    • 2002
  • Educators have found that the concept of randomness is often misunderstood by students. Chance recently pointed out that students should be introduced to the concept of randomness through the use of simulations. In this article, we studied various aspects of the probability distribution off linear random path in a circle and introduce some related simulations to guide student exploration and discovery. Consider a random line segment that crosses a circle with a certain radius. Perhaps it can be considered to be a path that an airplane shows up and flies into a random direction in a monitor. What is the expected amount of flying distance through the monitor, and the expected variation\ulcorner Are we monitoring what we see scientifically\ulcorner This article studies the probability distribution and some related aspects of a linear random path within a circular monitor. Some simulative activity is also introduced which can be used in a statistics or probability classes.

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