• Title/Summary/Keyword: variance approximation

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A Structural Design of Microgyroscope Using Kriging Approximation Model (크리깅 근사모델을 이용한 마이크로 자이로스코프의 구조설계)

  • Kim, Jong-Kyu;Lee, Kwon-Hee
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.7 no.4
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    • pp.149-154
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    • 2008
  • The concept of robust design was introduced by Dr. G. Taguchi in the late 1940s, and his technique has become commonly known as the Taguchi method or the robust design. In this research, a robust design procedure for microgyroscope is suggested based on the kriging and optimization approaches. The kriging interpolation method is introduced to obtain the surrogate approximation model of true function. Robustness is calculated by the kriging model to reduce real function calculations. For this, objective function is represented by the probability of success, thus facilitating robust optimization. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method.

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Performance degradation caused by coefficient approximation in Sliding-DFT based phasor measurement (순환 DFT 기반의 동기 위상 측정에 있어서 계수 근사에 따른 성능 열화 분석)

  • Kim, Chong-Yun;Chang, Tae-Gyu
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.4
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    • pp.470-476
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    • 2002
  • This paper presents an analysis of the performance degradation of coefficient approximation and frequency deviation in phase measurement algorithm based on Sliding-DFT. The analytic derivation is based on the statistics of the error dynamic equation that describes the error propagation of the recursion. The analysis result is intended to obtain a closed-form equation of error variance in terms of the number of bits used in coefficient approximation, the length of the DFT data block, and noise. It is verified with data obtained from the computer simulations.

Phase Noise Analysis in the OFDM Communication System (OFDM 통신시스템에서 위상 잡음분석)

  • 이영선;유흥균;정영호;함영권
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.15 no.11
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    • pp.1043-1050
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    • 2004
  • In this paper, Phase noise is analyzed and a novel approach of the nonlinear approximation including second order term of phase noise is presented to analyze and quantize system performance. As results, in QPSK-OFDM system, when PLL loop bandwidth is 5.0 Hz, 1.0 kHB, 0.5 kHz respectively, there are about 0.6 dB, 1.0 dB, 1.7 dB SNR penalties at BER=10$\^$-4/ compared with system without phase noise in AWGN channel. In 16QAM modulation, there are about 1.9 dB, 3.2 dB, 6.7 dB SNR penalties at BER=10$\^$-4/ respectively. At QPSK-OFDM system, comparing the previous linear approximation method with our proposed nonlinear approximation method, there is similar BER performance at phase noise variance lower than 0.02, but certain difference occurs as variance increases more than 0.02. Furthermore, analytical BER results closely match with simulation results in the OFDM system employing QPSK and 16qAM modulation. And, BER performance of QPSK-OFDM system is considerably degraded because of the BER error floor if the phase noise variance becomes larger than 0.03.

Measurement Error Variance Estimation Based on Complex Survey Data with Subsample Re-Measurements

  • Heo, Sunyeong;Eltinge, John L.
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.553-566
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    • 2003
  • In many cases, the measurement error variances may be functions of the unknown true values or related covariates. This paper considers design-based estimators of the parameters of these variance functions based on the within-unit sample variances. This paper devotes to: (1) define an error scale factor $\delta$; (2) develop estimators of the parameters of the linear measurement error variance function of the true values under large-sample and small-error conditions; (3) use propensity methods to adjust survey weights to account for possible selection effects at the replicate level. The proposed methods are applied to medical examination data from the U.S. Third National Health and Nutrition Examination Survey (NHANES III).

Wavelet-Based Face Recognition by Divided Area (웨이브렛을 이용한 공간적 영역분할에 의한 얼굴 인식)

  • 이성록;이상효;조창호;조도현;이상철
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2307-2310
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    • 2003
  • In this paper, a method for face recognition based on the wavelet packet decomposition is proposed. In the proposed method, the input image is decomposed by the 2-level wavelet packet transformation and then the face areas are defined by the Integral Projection technique applied to each of the 1-level subband images, HL and LH. After the defined face areas are divided into three areas, called top, bottom, and border, the mean and the variance of the three areas of the approximation image are computed, and the variance of the single predetermined face area for the rest of 15 detail images, from which the feature vectors of statistical measure are extracted. In this paper we use the wavelet packet decomposition, a generalization of the classical wavelet decomposition, to obtain its richer signal analysis features such as discontinuity in higher derivatives, self-similarity, etc. And we have shown that even with very simple statistical features such as mean values and variance we can make an excellent basis for face classification, if an appropriate probability distance is used.

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Small sample likelihood based inference for the normal variance ratio

  • Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.911-918
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    • 2013
  • This study deals with the small sample likelihood based inference for the ratio of two normal variances. The small sample likelihood inference is an approximation method. The signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic, which converge to standard normal distribution, are proposed for the normal variance ratio. Through the simulation study, the coverage probabilities of confidence interval and power of the exact, the signed log-likelihood and the modified signed log-likelihood ratio statistic will be compared. A real data example will be provided.

Estimation of error variance in nonparametric regression under a finite sample using ridge regression

  • Park, Chun-Gun
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1223-1232
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    • 2011
  • Tong and Wang's estimator (2005) is a new approach to estimate the error variance using least squares method such that a simple linear regression is asymptotically derived from Rice's lag- estimator (1984). Their estimator highly depends on the setting of a regressor and weights in small sample sizes. In this article, we propose a new approach via a local quadratic approximation to set regressors in a small sample case. We estimate the error variance as the intercept using a ridge regression because the regressors have the problem of multicollinearity. From the small simulation study, the performance of our approach with some existing methods is better in small sample cases and comparable in large cases. More research is required on unequally spaced points.

Selection of Survival Models for Technological Development (기술발전에 따른 생존모형 선정)

  • Oh, H.S.;Kim, C.S.;Rhee, H.K.;Yim, D.S.;Cho, J.H.
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.32 no.4
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    • pp.184-191
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    • 2009
  • In a technological driven environment, a depreciation estimate which is based on traditional life analysis results in a decelerated rate of capital recovery. This time pattern of technological growths models needs to be incorporated into life analysis framework especially in those industries experiencing fast technological changes. The approximation technique for calculating the variance can be applied to the six growth models that were selected by the degree of skewness and the transformation of the functions. For the Pearl growth model, the Gompertz growth model, and the Weibull growth model, the errors have zero mean and a constant variance over time. However, transformed models like the linearized Fisher-Pry model, the linearized Gompertz growth model, and the linearized Weibull growth model have increasing variance from zero to that point at which inflection occurs. It can be recommended that if the variance of error over time is increasing, then a transformation of observed data is appropriate.

Fractal Image Compression Using Adaptive Selection of Block Approximation Formula (블록 근사화식의 적응적 선택을 이용한 프랙탈 영상 부호화)

  • Park, Yong-Ki;Park, Chul-Woo;Kim, Doo-Young
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.12
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    • pp.3185-3199
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    • 1997
  • This paper suggests techniques to reduce coding time which is a problem in traditional fractal compression and to improve fidelity of reconstructed images by determining fractal coefficient through adaptive selection of block approximation formula. First, to reduce coding time, we construct a linear list of domain blocks of which characteristics is given by their luminance and variance and then we control block searching time according to the first permissible threshold value. Next, when employing three-level block partition, if a range block of minimum partition level cannot find a domain block which has a satisfying approximation error, we choose new approximation coefficients using a non-linear approximation of luminance term. This boosts the fidelity. Our experiment employing the above methods shows enhancement in the coding time more than two times over traditional coding methods and shows improvement in PSNR value by about 1-3dB at the same com- pression rate.

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Change of stochastic properties of MEMS structure in terms of dimensional variations using function approximation moment method (함수 근사 모멘트 기법을 활용한 치수 분포에 따른 MEMS 구조물의 통계적 특성치 변화에 관한 연구)

  • Huh J.S.;Kwak B.M.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.602-606
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    • 2005
  • A systematic procedure of probability analysis for general distributions is developed based on the first four moments estimated from polynomial interpolation of the system response function and the Pearson system. The function approximation is based on a specially selected experimental region for accuracy and the number of function evaluations is taken equal to that of the unknown coefficient for efficiency. For this purpose, three error-minimizing conditions are proposed and corresponding canonical experimental regions are formed for popular probability. This approach is applied to study the stochastic properties of the performance functions of a MEMS structure, which has quite large fabrication errors compared to other structures. Especially, the vibratory micro-gyroscope is studied using the statistical moments and probability density function (PDF) of the performance function to be the difference between resonant frequencies corresponding to sensing and driving mode. The results show that it is very sensitive to the fabrication errors and that the types of PDF of each variable also affect the stochastic properties of the performance function although they have same the mean and variance.

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