• Title/Summary/Keyword: PDF Method

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Parametric study based on synthetic realizations of EARPG(1)/UPS for simulation of extreme value statistics

  • Seong, Seung H.
    • Wind and Structures
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    • v.2 no.2
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    • pp.85-94
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    • 1999
  • The EARPG(1)/UPS was first developed by Seong (1993) and has been tested for wind pressure time series simulations (Seong and Peterka 1993, 1997, 1998) to prove its excellent performance for generating non-Gaussian time series, in particular, with large amplitude sharp peaks. This paper presents a parametric study focused on simulation of extreme value statistics based on the synthetic realizations of the EARPG(1)/UPS. The method is shown to have a great capability to simulate a wide range of non-Gaussian statistic values and extreme value statistics with exact target sample power spectrum. The variation of skewed long tail in PDF and extreme value distribution are illustrated as function of relevant parameters.

Inverse estimation of boundary characteristics by using underwater reverberation signals (수중 잔향음신호를 이용한 경계면 상태 역추정 알고리즘)

  • 김상균
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1996.06a
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    • pp.45-50
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    • 1996
  • 천해에서 얻은 잔향음신호를 역추정 알고리즘으로 분석하여 자료수집 당시의 환경 변수인 해상풍의 세기와 해저면의 상태를 추정하는 방법에 대하여 기술하였다. 소오나 시스템과 잔향음신호 수집 당시의 환경 자료를 알고 있다면 음원에서 방사된 음파가 해수면에 처음 도달하는 시간과 수평입사각을 multipath eigenray model에 의해서 계산할 수 있고 이 정보를 이용하여 수신된 잔향음 신호를 분석하여 해수면에 의한 산란잔향음 준위와 시간을 계산할 수 있다. 해수면 후방산란강도는 수평입사각, 음원의 주파수, 해상풍의 세기 등에 의해 특징지어지며 계산된 잔향음 준위로부터 소오나 방정식을 이용하여 후방산란강도를 알아낼 수 있다. 이 후방산란강도를 입력자료로 하여 Method of Small Perturbation이론과 Chapman과 Harris가 유도한 실험식을 사용하여 입력된 값과 일치할 때까지 후방산란강도를 계산하여 이때의 환경변수를 찾아내었다. 한편 해저면 잔향음신호는 표준화된 후방산란강도값들의 PDF를 만들어 그 분포양상을 분석하였다. 본 논문에서 사용된 알고리즘의 검증을 위해서는 보다 다양한 환경하에서 실시된 많은 음향괸측자료를 필요로 한다.

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Estimation of Radar Cross Section for a Swerving 1 Target

  • Jung, Young-Hun;Hong, Young-Ho
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2001.05a
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    • pp.232-236
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    • 2001
  • In this paper, we consider the problem of estimation of average radar cross section (RCS) for Swerling 1 fluctuation model, based on the maximum likelihood (ML) estimation method. In a mathematical development we take into account the event that target strength is lower than detection threshold, or the target is not detected. Our ML estimation for the SWR uses the score function that is the joint probability-pdf of the events and random variables. The solution to the ML estimation reduces to an expression in the from of a contraction mapping. The computational efficiency of the contraction mapping theorem is significant in computing the ML estimation as compared with other root-finding algorithms fur most radar tracking conditions.

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A Study On the Simulation Model of the Transformation of Random Variables Using FBI (Fortran Based Interpreter) (FBI(Fortran Based Interpreter)를 이용한 확률변수 변환의 시뮬레이션 모델에 관한 연구)

  • Kim, Won-Gyeong
    • Journal of Korean Institute of Industrial Engineers
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    • v.13 no.2
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    • pp.105-115
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    • 1987
  • Although there are many theoretical methods for the transformation of random variables. it is difficult to find probability density functions for the new random variables because of the complexity in mathematics. The author developed a simulation model solving the above difficulties using FBI (Fortran Based Interpreter) routines. The FBI is a kind of language Interpreter analyzing the arithmetic statement in character data forms. In this paper. the FBI routines will be explained and the structure and applications of simulation model will be also demonstrated. Polynomial curve fitting method is applied to define the probability density function which can not be defined by well-known pdf. This program can also be used for instructing mathematical statistics and identifying distribution of the simulated data.

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M-ary DPSK Error Performances with Noise and Interference (잡음 및 간섭도에 의한 M상 DPSK 시스템의 오율 특성)

  • ;森永規彦, 滑川敏彦
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.16 no.5
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    • pp.12-17
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    • 1979
  • This paper presents the investigation of the theoretical symbol error performances of an M-ary differential phase-shift-keyed(DPSK) system in an interference environment. A simple method is transmitted over a nondistroting channel, but additively corrupted by Gaussian noise and cochannel interference. Computed DPSK symbol error performance results for M=2, 4, and 8 are compared with the corresponding curves for coherent phase-shift-Keyed(CPSK) system as a function of carrier-to-noise power ratio(CNR) with carrier-to-interferer power ratio(CIR) as a parameter. Comparisons between DPSK systems reveal, as we might expect, that DPSK system suffers more degradation.

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Blind Signal Processing for Impulsive Noise Channels

  • Kim, Nam-Yong;Byun, Hyung-Gi;You, Young-Hwan;Kwon, Ki-Hyeon
    • Journal of Communications and Networks
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    • v.14 no.1
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    • pp.27-33
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    • 2012
  • In this paper, a new blind signal processing scheme for equalization in fading and impulsive-noise channel environments is introduced based on probability density functionmatching method and a set of Dirac-delta functions. Gaussian kernel of the proposed blind algorithm has the effect of cutting out the outliers on the difference between the desired level values and impulse-infected outputs. And also the proposed algorithm has relatively less sensitivity to channel eigenvalue ratio and has reduced computational complexity compared to the recently introduced correntropy algorithm. According to these characteristics, simulation results show that the proposed blind algorithm produces superior performance in multi-path communication channels corrupted with impulsive noise.

Verification and estimation of a posterior probability and probability density function using vector quantization and neural network (신경회로망과 벡터양자화에 의한 사후확률과 확률 밀도함수 추정 및 검증)

  • 고희석;김현덕;이광석
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.45 no.2
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    • pp.325-328
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    • 1996
  • In this paper, we proposed an estimation method of a posterior probability and PDF(Probability density function) using a feed forward neural network and code books of VQ(vector quantization). In this study, We estimates a posterior probability and probability density function, which compose a new parameter with well-known Mel cepstrum and verificate the performance for the five vowels taking from syllables by NN(neural network) and PNN(probabilistic neural network). In case of new parameter, showed the best result by probabilistic neural network and recognition rates are average 83.02%.

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System And Method For Sharing Presentation Using Cloud Service (클라우드 서비스를 활용한 프레젠테이션 실시간 공유 시스템 및 방법)

  • Lim, ChangBin;Kim, WonJin;Kang, AhReum;Lee, SangHo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.11a
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    • pp.238-240
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    • 2014
  • 회의 진행 시, 회의 참석자의 컴퓨터에 별다른 애플리케이션의 설치 없이 인터넷 URL에 접속함으로써 회의 자료를 공유하여 원활한 회의 진행을 제공한다. 회의진행자는 클라우드 서버의 파일을 이용하여 회의를 진행하고 이 파일은 서버를 거쳐 PDF파일로 변환되어 인터넷 브라우저에 표현된다. 회의 진행자는 그리기 기능을 이용하여 프레젠테이션에 설명을 덧붙일 수 있다. 그리기 기능과 함께 프레젠테이션의 페이지 넘김 기능도 실시간으로 회의 참석자의 인터넷 브라우저에 표현 된다.

Modeling Quantization Error using Laplacian Probability Density function (Laplacian 분포 함수를 이용한 양자화 잡음 모델링)

  • 최지은;이병욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.11A
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    • pp.1957-1962
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    • 2001
  • Image and video compression requires quantization error model of DCT coefficients for post processing, restoration or transcoding. Once DCT coefficients are quantized, it is impossible to recover the original distribution. We assume that the original probability density function (pdf) is the Laplacian function. We calculate the variance of the quantized variable, and estimate the variance of the DCT coefficients. We can confirm that the proposed method enhances the accuracy of the quantization error estimation.

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Compare Three Method for Keyword Summary (키워드 요약의 세 가지 방법론 비교)

  • Kang, Jong-Reul;Nam, Ji-Seong;Park, Gi-na;Kim, Woongsup
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.852-854
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    • 2019
  • 본 논문은 정확한 연관검색어를 보여주지 못하는 기존의 검색에서 벗어나기 위해 이미지와 PDF에서 텍스트를 추출하고 키워드 요약하는 방법을 사용하였다. 텍스트를 키워드로 요약하는 알고리즘으로는 TextRank, LSA, MMR을 사용하였고, 세 가지 방법으로 키워드를 요약하고 키워드 요약 결과와 Query의 코사인 유사도를 이용하여 추출한 문서와 Query와의 연관성을 확인하여 세 가지 알고리즘을 비교하였다.