• 대한수학회보
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• 제34권4호
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• pp.573-581
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• 1997

This paper is concerned with the strong consistency of the $L_1$-norm estimators for the nonlinear regression models when dependent variables are subject to censoring, and provides the sufficient conditions which ensure the strong consistency of $L_1$-norm estimators of the censored regression models.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제9권1호
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• pp.81-90
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• 2002

The least informative (favorable) distributions, minimizing Fisher information for a multivariate location parameter, are derived in the parametric class of the exponential-power spherically symmetric distributions under the following characterizing restrictions; (i) a bounded variance, (ii) a bounded value of a density at the center of symmetry, and (iii) the intersection of these restrictions. In the first two cases, (i) and (ii) respectively, the least informative distributions are the Gaussian and Laplace, respectively. In the latter case (iii) the optimal solution has three branches, with relatively small variances it is the Gaussian, them with intermediate variances. The corresponding robust minimax M-estimators of location are given by the $L_2$-norm, the $L_1$-norm and the $L_{p}$ -norm methods. The properties of the proposed estimators and their adaptive versions ar studied in asymptotics and on finite samples by Monte Carlo.

• 한국통신학회논문지
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• 제21권6호
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• pp.1522-1532
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• 1996

In this paper, we compare the performance of channel estimators with the L$_{1}$-norm and L$_{2}$-norm criteria in impulaive noise environment, and show than the L$_{1}$-norm criterion is appropriate for that situation. Also, it is shown that the performance of the conventional maximum likelihood sequence detector(MLSD) can be improved by applying the same principle to mobile channels. That is, the performance of the conventional MLSD, which is known to be optimal under the Gaussian noise assumption, degrades in the impulsive noise of radio mobile communication channels. So, we proposed the MLSD which can reduce the effect of impulsive noise effectively by applying the results of channel estimators. Finally, it is confirmed by computer simulation that the performance of MLSD is significantly affected depending on the types of branch metrics, and that, in the impulsive noise environments, the proposed one with new branch metrics performs better thatn the conventional branch metric, l y(k)-s(k) l$^{[-992]}$ .

• 한국측량학회지
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• 제35권6호
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• pp.573-580
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• 2017

GPS 관측값을 이용하여 측위를 하는 경우 조정계산이 수반되면 이때 관측오차에 대한 정확한 모델링이 필수적이다. 본 연구에서는 GPS 관측타입별 관측오차를 분석하기 위해 MINQUE(Minimum Norm Quadratic Unbiased Estimators) 방법을 사용하였으며 단기선 GPS측위 모델을 기반으로 하였다. C1, P2, L1, L2 관측타입에 대해 각각 단위분산을 계산하였으며 그 결과 관측오차는 각각 22.3cm, 27.6cm, 2.5cm, 2.2cm로 나타났다. 단위분산 계산에는 대용량의 컴퓨터 메모리와 복잡한 계산이 필요하다. 이러한 단점을 극복하기 위해 epoch별로 단위분산을 추정하였으며 결과를 분석함으로써 epoch별 계산방법의 유효성을 검증하였다. 분석 결과, 계산된 결과값에 차이가 있긴 했으나 그 차이가 비교적 작기 때문에 대부분의 GPS 응용분야에서의 활용에는 문제가 없을 것으로 판단된다.