• ETRI Journal
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• 제33권1호
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• pp.27-31
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• 2011

This paper addresses estimating the frequency of a cisoid in the presence of white Gaussian noise, which has numerous applications in communications, radar, sonar, and instrumentation and measurement. Due to the nonlinear nature of the frequency estimation problem, there is threshold effect, that is, large error estimates or outliers will occur at sufficiently low signal-to-noise ratio (SNR) conditions. Utilizing the ideas of averaging to increase SNR and weighted linear prediction, an optimal frequency estimator with smaller threshold SNR is developed. Computer simulations are included to compare its mean square error performance with that of the maximum likelihood (ML) estimator, improved weighted phase averager, generalized weighted linear predictor, and single weighted sample correlator as well as Cramer-Rao lower bound. In particular, with smaller computational requirement, the proposed estimator can achieve the same threshold and estimation performance of the ML method.

• Journal of the Korean Data and Information Science Society
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• 제23권1호
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• pp.219-225
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• 2012

We derive approximate maximum likelihood estimators of two parameters in a weighted exponential distribution, and derive the density function for the ratio Y=(X+Y) of two independent weighted exponential random variables X and Y, and then observe the skewness of the ratio density.

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.21-32
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• 1997

Robust regression based on M-estimator reduces and/or bounds the influence of outliers in the y-direction only. Therefore, when several influential observations exist, diagnostics in the robust regression is required in order to detect them. In this paper, we propose influence diagnostics in the robust regression based on M-estimator and its one-step version. Noting that M-estimator can be obtained through iterative weighted least squares regression by using internal weights, we apply the weighted least squares (WLS) regression diagnostics to robust regression.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.371-382
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• 2005

The paper compares the performance of some widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained Bayes estimator by means of a new measurement under squared error loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• 전자공학회논문지A
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• 제33A권5호
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• pp.31-43
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• 1996

In this paper, we analyze the delay characteristics of the multimdedia traffic in B-ISDN, and propose a weighted variable-size window estimator considering the QoS characteristics of the media and the variable delay characteristics of the networks, and present a delay estimator-based synchronization protocol for the efficient synchronization in ATM-based B-ISDN. The proposed estimator assigns a high weight value to recent cells arrived in the receiver, and suitably adjusts window size in order to efficiently adapt to delay variation by the prameter to detect the delay variation of the networks. The proposed synchronization protocol estimates end-to-end delay by the weighted variable-size window estimator, and dynamically schedules th evirtual channel of the transmitter to playout multimedia data on time in the receiver. Also, we evaluate the performance of the delay estimator, which is the most importnat functional element in our proposed synchronization protocol, by the simulation and analyze the results of the simulation.

• Structural Engineering and Mechanics
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• 제34권1호
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• pp.1-14
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• 2010

The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

• 응용통계연구
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• 제19권1호
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• pp.97-110
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• 2006

대부분의 자료는 여러가지 원인으로 인한 특이치로 오염되어 있으며, 이러한 상황에서 신뢰성 있는 추정량을 얻어내고 이에 대한 통계적 추론을 시행하는 것은 중요한 문제이다. 그러나 이제까지 제안된 로버스트 회귀추정량들은 계산상의 어려움과 정규오차모형에서 최소제곱추정량에 비하여 떨어지는 효율성때문에 통계적 추론의 정확성을 확신할 수 없었다. 최근 제안된 Lee(2004)의 가중자기조율회귀추정량(weighted self-tuning estimator, WSTE)은 다른 로버스트 회귀추정량에 비하여 정확한 계산과정과 그에 따른 추정량의 점근적 정규성 및 고붕괴점을 갖는다. 그러나 통계적 추론을 위하여 이제까지 널리 사용해왔던 로버스트 추정량에 기반한 가중최소제곱추정방법(weighted least squares estimator)은 WSTE에서조차 정규오차모형하에서 최소제곱추정량과 동일한 수준의 효율성을 제공해주지 는 못한다. 본 논문에서는 WSTE에 기반한 또다른 통계적 추론 방법을 제안하고, 이 방법을 사용함으로써 정규오차모형 및 대표본에서 보다 정확한 결과를 얻을 수 있음을 몬테칼로 모의실험을 통해 제시하였다.

• Structural Engineering and Mechanics
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• 제37권4호
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• pp.351-365
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• 2011

This study proposes an inverse estimation method for the input forces of a fixed beam structural system. The estimator includes the fuzzy Kalman Filter (FKF) technology and the fuzzy weighted recursive least square method (FWRLSM). In the estimation method, the effective estimator are accelerated and weighted by the fuzzy accelerating and weighting factors proposed based on the fuzzy logic inference system. By directly synthesizing the robust filter technology with the estimator, this study presents an efficient robust forgetting zone, which is capable of providing a reasonable trade-off between the tracking capability and the flexibility against noises. The period input of the fixed beam structure system can be effectively estimated by using this method to promote the reliability of the dynamic performance analysis. The simulation results are compared by alternating between the constant and adaptive and fuzzy weighting factors. The results demonstrate that the application of the presented method to the fixed beam structure system is successful.

• 대한전기학회논문지
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• 제41권9호
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• pp.1021-1030
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• 1992

When using a least squares estimator with exponential forgetting factor to identify continuous-time deterministic system, the problem of determining minimum eigenvalue is described in this paper. It is well known fact that the convergence rate of parameter estimates relies on various factors consisting of the estimator and especially, theirproperties can be directly affected by all eigenvalues in the parameter error differential equation. Fortunately, there exists only one adjusting eigenvalue in the given estimator and then, the parameter convergence rates depend on this minimum eigenvalue. In this note, a new result to determine the minimum eigenvalue is proposed. Under the assumption that the input has as many spectral lines as the number of parameter estimates, it can be proven that the minimum eigenvalue converges to a constant value, which is a function of the forgetting factor and the parameter estimates number.