• Title/Summary/Keyword: Probability density estimation

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Structural reliability estimation based on quasi ideal importance sampling simulation

  • Yonezawa, Masaaki;Okuda, Shoya;Kobayashi, Hiroaki
    • Structural Engineering and Mechanics
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    • v.32 no.1
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    • pp.55-69
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    • 2009
  • A quasi ideal importance sampling simulation method combined in the conditional expectation is proposed for the structural reliability estimation. The quasi ideal importance sampling joint probability density function (p.d.f.) is so composed on the basis of the ideal importance sampling concept as to be proportional to the conditional failure probability multiplied by the p.d.f. of the sampling variables. The respective marginal p.d.f.s of the ideal importance sampling joint p.d.f. are determined numerically by the simulations and partly by the piecewise integrations. The quasi ideal importance sampling simulations combined in the conditional expectation are executed to estimate the failure probabilities of structures with multiple failure surfaces and it is shown that the proposed method gives accurate estimations efficiently.

A Modulation and Channel State Estimation Algorithm Using the Received Signal Analysis in the Blind Channel (블라인드 채널에서 수신 신호 분석 기법을 사용한 변조 및 채널 상태 추정 알고리즘)

  • Cho, Minhwan;Nam, Haewoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.11
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    • pp.1406-1409
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    • 2016
  • In this paper, we propose the heuristic signal grouping algorithm to estimate channel state value over full blind communication situation which means that there is no information about the modulation scheme and the channel state information between the transmitter and the receiver. Hereafter, using the constellation rotation method and the probability density function(pdf) the modulation scheme is determined to perform automatic modulation classification(AMC). Furthermore, the modulation type and a channel state value estimation capability is evaluated by comparing the proposed scheme with other conventional techniques from the simulation results in terms of the symbol error rate(SER) and the root mean square error (RMSE).

The Estimation of the Surface Sidelobe Clutter Distribution for the HPRF Waveform of the M/W Seeker (마이크로파 탐색기의 HPRF 파형에 대한 지표면 부엽 클러터 분포의 추정)

  • Kim, Tae-Hyung;Byun, Young-Jin;Yi, Jae-Woong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.12 no.1
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    • pp.1-7
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    • 2009
  • Tracking and detecting targets by the M/W seeker is affected by the clutter reflecting from the earth's surface. In order to detect the look-down retreating targets, which appear in the sidelobe clutter region, in the M/W seeker of High PRF mode, it is necessary to understand statistical characteristics of the surface sidelobe clutter. Statistical analysis of sidelobe clutter is conducted for several configurations of the surface using data obtained by the CFT (Captive Flight Test) of the M/W seeker in High PRF mode. The probability density function(PDF) fitting is conducted for several configuration and conditions of the surface. PDFs and PDF parameters, which best describe statistical distribution of sidelobe clutter, are estimated.

An Algorithm of Score Function Generation using Convolution-FFT in Independent Component Analysis (독립성분분석에서 Convolution-FFT을 이용한 효율적인 점수함수의 생성 알고리즘)

  • Kim Woong-Myung;Lee Hyon-Soo
    • The KIPS Transactions:PartB
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    • v.13B no.1 s.104
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    • pp.27-34
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    • 2006
  • In this study, we propose this new algorithm that generates score function in ICA(Independent Component Analysis) using entropy theory. To generate score function, estimation of probability density function about original signals are certainly necessary and density function should be differentiated. Therefore, we used kernel density estimation method in order to derive differential equation of score function by original signal. After changing formula to convolution form to increase speed of density estimation, we used FFT algorithm that can calculate convolution faster. Proposed score function generation method reduces the errors, it is density difference of recovered signals and originals signals. In the result of computer simulation, we estimate density function more similar to original signals compared with Extended Infomax and Fixed Point ICA in blind source separation problem and get improved performance at the SNR(Signal to Noise Ratio) between recovered signals and original signal.

A Comparison on the Differential Entropy

  • Kim, Dae-Hak
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.3
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    • pp.705-712
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    • 2005
  • Entropy is the basic concept of information theory. It is well defined for random varibles with known probability density function(pdf). For given data with unknown pdf, entropy should be estimated. Usually, estimation of entropy is based on the approximations. In this paper, we consider a kernel based approximation and compare it to the cumulant approximation method for several distributions. Monte carlo simulation for various sample size is conducted.

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Smoothing Parameter Selection in Nonparametric Spectral Density Estimation

  • Kang, Kee-Hoon;Park, Byeong-U;Cho, Sin-Sup;Kim, Woo-Chul
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.231-242
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    • 1995
  • In this paper we consider kernel type estimator of the spectral density at a point in the analysis of stationary time series data. The kernel entails choice of smoothing parameter called bandwidth. A data-based bandwidth choice is proposed, and it is obtained by solving an equation similar to Sheather(1986) which relates to the probability density estimation. A Monte Carlo study is done. It reveals that the spectral density estimates using the data-based bandwidths show comparatively good performance.

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A Study of Log-Fourier Deconvolution

  • Ja Yong Koo;Hyun Suk Park
    • Communications for Statistical Applications and Methods
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    • v.4 no.3
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    • pp.833-845
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    • 1997
  • Fourier expansion is considered for the deconvolution problem of estimating a probability density function when the sample observations are contaminated with random noise. In the log-Fourier method of density estimation for data without noise, the logarithm of the unknown density function is approximated by a trigonometric function, the unknown parameters of which are estimated by maximum likelihood. The log-Fourier density estimation method, which has been considered theoretically by Koo and Chung (1997), is studied for the finite-sample case with noise. Numerical examples using simulated data are given to show the performance of the log-Fourier deconvolution.

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ECG Denoising by Modeling Wavelet Sub-Band Coefficients using Kernel Density Estimation

  • Ardhapurkar, Shubhada;Manthalkar, Ramchandra;Gajre, Suhas
    • Journal of Information Processing Systems
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    • v.8 no.4
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    • pp.669-684
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    • 2012
  • Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.

A New Gradient Estimation of Euclidean Distance between Error Distributions (오차확률분포 사이 유클리드 거리의 새로운 기울기 추정법)

  • Kim, Namyong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.8
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    • pp.126-135
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    • 2014
  • The Euclidean distance between error probability density functions (EDEP) has been used as a performance criterion for supervised adaptive signal processing in impulsive noise environments. One of the drawbacks of the EDEP algorithm is a heavy computational complexity due to the double summation operations at each iteration time. In this paper, a recursive method to reduce its computational burden in the estimation of the EDEP and its gradient is proposed. For the data block size N, the computational complexity for the estimation of the EDEP and its gradient can be reduced to O(N) by the proposed method, while the conventional estimation method has $O(N^2)$. In the performance test, the proposed EDEP and its gradient estimation yield the same estimation results in the steady state as the conventional block-processing method. The simulation results indicates that the proposed method can be effective in practical adaptive signal processing.

A Study on the Evaluation of Linear Cumulative Damage Factor of Membrane Type LNG Tank by use of Probability Density Function (확률밀도함수를 이용한 멤브레인방식 LNG탱크의 선형누적손상도 평가에 관한 연구)

  • 김종호
    • Journal of Advanced Marine Engineering and Technology
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    • v.28 no.6
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    • pp.993-999
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    • 2004
  • The estimation of fatigue life at the design stage of membrane type LNG tank is very important in order to arrive at feasible and cost effective solutions considering the total lifetime of the tank. In this study, the practical procedure of fatigue life prediction by use of cumulative damage factors based on Miner-Palmgren hypothesis and probability density function has been shown with the corner region of Gaz Transport Membrane type LNG tank being used as an example. In particular the parameters of Weibull distribution that determine the stress spectrum are discussed. The main results obtained from this study are as follows: 1. The recommended value for the shape parameter of Weibull distribution for the LNG tank is 1.1 in case of using the direct calculation method proposed in this study. 2. The calculated fatigue life is influenced by the shape parameter of Weibull distribution and stress block. The safe fatigue design can be achieved by using higher value of shape parameter and the stress blocks divided into more stress blocks.