• 한국통신학회논문지
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• 제38A권12호
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• pp.1013-1020
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• 2013

본 논문에서는 대역 확산 신호를 위한 고유치 해석 기반의 초 분해능 지연 시간 추정(super-resolution time delay estimation) 알고리즘을 개발하고 각 알고리즘의 성능을 비교, 분석한다. 먼저, 고유치 해석 기반의 대표적인 도래각 추정 알고리즘인 MUSIC, ESPRIT, Minimum-Norm을 이용하여 초 분해능 지연 시간 추정 알고리즘을 개발하고 직접 대역확산 방식의 ISO/IEC 24730-2.1 실시간 위치 추적 시스템 (real-time locating system: RTLS)에 적용하여 RTLS 환경에서 각 알고리즘의 성능을 시뮬레이션을 통해 비교, 분석한다. 시뮬레이션 결과로부터 세 알고리즘 모두 레일리이 분해능 한계 이내로 수신되는 다중 신호의 지연 시간을 모두 분리, 추정함을 알 수 있었다. 그러나, RTLS 환경에서는 MUSIC과 Minimum-Norm의 성능은 서로 비슷하나 ESPRIT은 두 알고리즘에 비해 성능이 현격히 저하됨을 알 수 있다.

• Journal of the Korean Statistical Society
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• 제16권2호
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• pp.80-91
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• 1987

Minimum $L_i$ norm estimation is a robust procedure ins the sense that it leads to an estimator which has greater statistical eficiency than the least squares estimator in the presence of outliers. And the $L_1$ norm estimator has some desirable statistical properties. In this paper a new computational procedure for $L_1$ norm estimation is proposed which combines the idea of reweighted least squares method and the linear programming approach. A modification of the projective transformation method is employed to solve the linear programming problem instead of the simplex method. It is proved that the proposed algorithm terminates in a finite number of iterations.

• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.373-385
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• 2006

To solve a class of nonlinear parameter estimation problems, a method combining the regularized structured nonlinear total least norm (RSNTLN) method and parameter separation scheme is suggested. The method guarantees the convergence of parameters and has an advantages in reducing the residual norm over the use of RSNTLN only. Numerical experiments for two models appeared in signal processing show that the suggested method is more effective in obtaining solution and parameter with minimum residual norm.

• 대한의용생체공학회:의공학회지
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• 제24권5호
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• pp.459-464
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• 2003

심자도 신호로부터 전류원의 분포를 복원하는 알고리듬을 구성하고 이를 WPW 증후군 환자에 대해 적용하여 임상적 유용성을 검토하였다. 40 채널 superconducting quantum interference device (SQUID) 미분계를 이용하여 심자도를 측정하고 minimum norm estimation (MNE) 알고리듬과 truncated singular value decomposition (SVD)을 적용하여 2 차원 평면에서의 전류원 분포를 구하였으며. 전류원의 분포가 실제 전류원의 정보를 잘 반영하고 있음을 시뮬레이션으로 확인하였다. 또한 좌심방과 좌심실 사이에 부전도로를 가진 WPW 증후군 환자의 심자도를 측정하여 수술 전후의 전류원 분포를 비교한 결과 수술 전에는 부전도로를 통한 비정상전류의 흐름을 볼 수 있었으나 부전도로를 절제한 후에는 더 이상 볼 수 없었다. 이 결과는 심자도 선호로부터 구한 전류원 분포가 심장의 전기 활동을 잘 반영하고 있으며 임상적으로 유용하게 활용 될 수 있음을 보여준다.

• 조명전기설비학회논문지
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• 제21권4호
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• pp.96-103
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• 2007

In this paper, we present a novel and numerically efficient algorithm for high resolution TOA(Time Of Arrival) estimation under indoor radio propagation channels. The proposed algorithm is not dependent on the structure of receivers, i.e, it can be used with either coherent or non-coherent receivers. The TOA estimation algorithm is based on a high resolution frequency estimation algorithm of Minimum-norm. The efficiency of the proposed algorithm relies on numerical analysis techniques in computing signal or noise subspaces. The algorithm is based on the two step procedures, one for transforming input data to frequency domain data and the other for estimating the unknown TOA using the proposed efficient algorithm. The efficiency in number of operations over other algorithms is presented. The performance of the proposed algorithm is investigated by means of computer simulations.. Throughout the analytic and computer simulation results, we show that the proposed algorithm exhibits superior performance in estimating TOA estimation with limited computational cost.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(5)
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• pp.124-126
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• 2000

The Minimum-Norm Least-Square(MNLS) approach based on lead field theory is an useful method to find an unique inverse solution for the measured magnetic field. The lead field depends on head geometry and location of sources and sensors. So, optimization of sensor array location is important issue for MNLS estimation. In this paper, we present an investigation for the optimization of sensor array location in computer simulation.

• Journal of the Korean Statistical Society
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• 제10권
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• pp.91-96
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• 1981

The development of Minimum Norm Quadratic Unbiased Estimation (MINQUE) has introduced a unified approach for the estimation of variance components in general linear models. The computational problem has been studied by Liu and Senturia (1977) and Goodnight (1978, setting a-priori values to 0). This paper further simplifies the computation and gives efficient and compact computational algorithm for the MINQUE and dispersion matrix in general linear random model.

• East Asian mathematical journal
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• 제5권1호
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• pp.95-110
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• 1989

In a general variance component model, nonnegative quadratic estimators of the components of variance are considered which are invariant with respect to mean value translaion and have minimum bias (analogously to estimation theory of mean value parameters). Here the minimum is taken over an appropriate cone of positive semidefinite matrices, after having made a reduction by invariance. Among these estimators, which always exist the one of minimum norm is characterized. This characterization is achieved by systems of necessary and sufficient condition, and by a cone restricted pseudoinverse. In models where the decomposing covariance matrices span a commutative quadratic subspace, a representation of the considered estimator is derived that requires merely to solve an ordinary convex quadratic optimization problem. As an example, we present the two way nested classification random model. An unbiased estimator is derived for the mean squared error of any unbiased or biased estimator that is expressible as a linear combination of independent sums of squares. Further, it is shown that, for the classical balanced variance component models, this estimator is the best invariant unbiased estimator, for the variance of the ANOVA estimator and for the mean squared error of the nonnegative minimum biased estimator. As an example, the balanced two way nested classification model with ramdom effects if considered.

• 대한전자공학회논문지SP
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• 제42권2호
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• pp.151-160
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• 2005

본 논문에서는 연속제거 알고리즘(successive elimination algerian)을 기반으로 하여 H.264 부호화기의 복잡도에서 가장 큰 비중을 차지하는 가변 블록에 대한 움직임 추정을 효율적으로 생략함으로써 고속으로 움직임 벡터를 탐색하는 기법을 제안한다. 제안된 기법은 7가지 모드의 가변 블록에 대하여 기존의 SEA를 계층적으로 적용한다. 즉, SEA를 사용해서 $4\times4$ 블록 단위로 SAD 또는 sum norm을 조합하고 이것을 각 모드의 최소 SAD 값과 비교 검색함으로써 불필요한 SAD 계산을 줄이는 방식이다. 그러므로 SEA의 SAD와 sum norm의 부등 관계에서 경계범위를 좁게 만들 수 있다. 단위 블록의 크기를 $4\times4$ 이하로 할 경우에는 경계 범위를 더욱 좁게 만들 수 있으나 계산량이 증가하는 단점이 있다. 제안된 기법을 적용했을 때에 각 실험영상에 따른 전체적인 계산량은 H.264의 고속 전역 탐색 방식에 비하여 약 $60\%\~70\%$의 일관된 감소가 있었다.

• Progress in Superconductivity
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• 제4권1호
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• pp.48-52
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• 2002

When applying a SQUID system for diagnosing heart disease, it is informative to obtain the source current distributions from the measured MCG (magnetocardiogram) signals since the bioelectric activity in the heart is generally represented by distributed current sources. In order to estimate the Primary current distribution in a heart, the minimum norm estimate was computed, assuming a source plane below the chest surface. In the simulation, current distributions, which were computed for the test dipoles represented well the essential feature of the test-current configurations. Source current reconstruction was performed for MCG signal of a healthy volunteer, which was recorded using a 40-channel SQUID system in a magnetically shielded room. It was found that the obtained current distribution is consistent with the electrical activity in a heart.