• Title/Summary/Keyword: Minimum Variance

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Uniformly Minimum Variance Unbiased Estimation for Distributions with Support Dependign on Two Parameters

  • Hong, Chong-Sun;Park, Hyun-Jip;Lee, Chong-Cheol
    • Journal of the Korean Statistical Society
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    • v.24 no.1
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    • pp.45-64
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    • 1995
  • When a random sample is taken from a certain class of discrete and continuous distributions whose support depend on two parameters, we could find that there exists the complete and sufficient statistic for parameters which belong to a certain class, and fomulate the uniformly minimum variance unbiased estimator (UMVUE) of any estimable function. Some UMVUE's of parametric functions are illustrated for the class of the distribution. Especially, we find that the UMVUE of some estimable parametric function from the truncated normal distribution could be expressed by the version of the Mill's ratio.

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Minimum Variance FIR Smoother for Model-based Signals

  • Kwon, Bo-Kyu;Kwon, Wook-Hyun;Han, Soo-Hee
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2516-2520
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    • 2005
  • In this paper, finite impulse response (FIR) smoothers are proposed for discrete-time systems. The proposed FIR smoother is designed under the constraints of linearity, unbiasedness, FIR structure, and independence of the initial state information. It is also obtained by directly minimizing the performance criterion with unbiased constraints. The approach to the MVF smoother proposed in this paper is logical and systematic, while existing results have heuristic assumption, such as infinite covariance of the initial state. Additionally, the proposed MVF smoother is based on the general system model that may have the singular system matrix and has both system and measurement noises. Thorough simulation studies, it is shown that the proposed MVF smoother is more robust against modeling uncertainties numerical errors than fixed-lag Kalman smoother which is infinite impulse response (IIR) type estimator.

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Robust adaptive control by single parameter adaptation and the stability analysis (단일계수적응을 통한 강건한 적응제어시의 설계및 안정성 해석)

  • 오준호
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.14 no.2
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    • pp.331-338
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    • 1990
  • In adaptive control, the lack of persistent and rich excitation causes the estimated parameters to drift, which degrade the performance of the system and may introduces instability to the system in a stochastic environment. To solve the problem of the parameter drift, the concept of single parameter adaptation is presented. For the parameter identification, a priori error is directly used for adaptation error. The structure of the controller is based upon the minimum variance control technique. The stability and robustness analysis is carried out by the sector stability theorem for the second order system. The computer simulation is performed to justify the theoretical analysis for the various cases.

Advanced Process Control of the Critical Dimension in Photolithography

  • Wu, Chien-Feng;Hung, Chih-Ming;Chen, Juhn-Horng;Lee, An-Chen
    • International Journal of Precision Engineering and Manufacturing
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    • v.9 no.1
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    • pp.12-18
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    • 2008
  • This paper describes two run-to-run controllers, a nonlinear multiple exponential-weight moving-average (NMEWMA) controller and a dynamic model-tuning minimum-variance (DMTMV) controller, for photolithography processes. The relationships between the input recipes (exposure dose and focus) and output variables (critical dimensions) were formed using an experimental design method, and the photolithography process model was built using a multiple regression analysis. Both the NMEWMA and DMTMV controllers could update the process model and obtain the optimal recipes for the next run. Quantified improvements were obtained from simulations and real photolithography processes.

Faults Detection in Hub Bearing with Minimum Variance Cepstrum (최소 분산 켑스트럼을 이용한 자동차 허브 베어링 결함 검출)

  • 박춘수;최영철;김양한;고을석
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.593-596
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    • 2004
  • Hub bearings not only sustain the body of a car, but permit wheels to rotate freely. Excessive radial or axial load and many other reasons can cause defects to be created and grown in each component. Therefore, vibration and noise from unwanted defects in outer-race, inner-race or ball elements of a Hub bearing are what we want to detect as early as possible. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing signal has periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

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Early Detection of Faults in a Ball Bearing System (베어링 시스템에서 결함을 초기에 진단하는 방법)

  • Choi, Young-Chul;Kim, Yang-Hann
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2000.06a
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    • pp.1102-1107
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    • 2000
  • The signals that can be obtained from a rotating machine often convey the information of machine. For example, if the machine under investigation has faults, then we can measure the signal which has a pulse train, embedded in noise. Therefore the ability to detect the fault signal in noise determines the degree of diagnosis level of rotating machine. In this paper, minimum variance cepstrum (MV cepstrum), which can easily detect impulse in noise, has been applied to detect the type of faults of ball bearing system. To test the performance of this technique, experiment has been performed for ball bearing elements that have man made faults. Results show that minimum variance cepstrum can easily detect the periodicity due to faults.

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The Three-Stage Cluster Randomized Response Model for Obtaining Sensitive Information

  • Lee, Gi Sung;Hong, Ki Hak;Son, Chang Kyoon;Jung, Young Mee
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.247-256
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    • 2003
  • In this study, we systemize the theoretical validity for applying RRM to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the costs are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them. We apply the three-stage cluster RRM to field survey and suggest some necessary points for practical use.

Multi-Channel Speech Enhancement Algorithm Using DOA-based Learning Rate Control (DOA 기반 학습률 조절을 이용한 다채널 음성개선 알고리즘)

  • Kim, Su-Hwan;Lee, Young-Jae;Kim, Young-Il;Jeong, Sang-Bae
    • Phonetics and Speech Sciences
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    • v.3 no.3
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    • pp.91-98
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    • 2011
  • In this paper, a multi-channel speech enhancement method using the linearly constrained minimum variance (LCMV) algorithm and a variable learning rate control is proposed. To control the learning rate for adaptive filters of the LCMV algorithm, the direction of arrival (DOA) is measured for each short-time input signal and the likelihood function of the target speech presence is estimated to control the filter learning rate. Using the likelihood measure, the learning rate is increased during the pure noise interval and decreased during the target speech interval. To optimize the parameter of the mapping function between the likelihood value and the corresponding learning rate, an exhaustive search is performed using the Bark's scale distortion (BSD) as the performance index. Experimental results show that the proposed algorithm outperforms the conventional LCMV with fixed learning rate in the BSD by around 1.5 dB.

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Length-biased Rayleigh distribution: reliability analysis, estimation of the parameter, and applications

  • Kayid, M.;Alshingiti, Arwa M.;Aldossary, H.
    • International Journal of Reliability and Applications
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    • v.14 no.1
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    • pp.27-39
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    • 2013
  • In this article, a new model based on the Rayleigh distribution is introduced. This model is useful and practical in physics, reliability, and life testing. The statistical and reliability properties of this model are presented, including moments, the hazard rate, the reversed hazard rate, and mean residual life functions, among others. In addition, it is shown that the distributions of the new model are ordered regarding the strongest likelihood ratio ordering. Four estimating methods, namely, method of moment, maximum likelihood method, Bayes estimation, and uniformly minimum variance unbiased, are used to estimate the parameters of this model. Simulation is used to calculate the estimates and to study their properties. Finally, the appropriateness of this model for real data sets is shown by using the chi-square goodness of fit test and the Kolmogorov-Smirnov statistic.

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Precision Stabilization Control of Servo-system by Using Friction Compensation (마찰보상을 통한 서어보제어계의 정밀 안정화 제어)

  • Kang, Min-Sig
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.3 s.96
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    • pp.109-115
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    • 1999
  • This paper presents a stabilization control designed to improve position stabilization performance of a position servo-system(turret) mounted on a manuvering platform(vehicle). In the consideration of the motion of the platform, a dynamic model of the stabilization system is derived and shows the viscous and stick-slip friction torques are the major source of stabilization errors. An extended generalized minimum variance control which consists of a feedforward disturbance compensation as well as a pole placement feedback control is suggested to reduce the stabilization errors caused from the friction disturbances. This modeling and control are applied to a small experimental set-up and the experimental results confirm the accuracy of the model and the effectiveness of the suggested control.

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