• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1013-1020
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• 2013

In this paper the super-resolution time delay estimation algorithms based on eigen-analysis are developed for spread spectrum signals along with their comparative performance analysis. First, we shall develop super-resolution time delay estimation algorithms using the representative eigen-analysis based AOA (angle-of-arrival) estimation algorithms such as MUSIC, Minimum-Norm, and ESPRIT, and apply them to the ISO/IEC 24730-2.1 real-time locating system (RTLS) employing a direct sequence spread spectrum (DS-SS) technique to compare their performances in RTLS environments. Simulation results illustrate that all the three algorithms can resolve multipath signals whose delay differences are even smaller than the Rayleigh resolution limit. Simulation results also show that MUSIC and Minimum-Norm provide a similar performance while ESPRIT is inferior to both algorithms in RTLS environments.

• Journal of the Korean Statistical Society
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• v.16 no.2
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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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• v.22 no.1_2
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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.

• Journal of Biomedical Engineering Research
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• v.24 no.5
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• pp.459-464
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• 2003

The source current distribution in a heart was reconstructed from the magnetocardiogram (MCG) and its clinical usefulness was demonstrated. MCG was measured using 40-channel superconducting quantum interference device (SQUID) gradiometers for a patient of Wolff-Parkinson-White (WPW) syndrome, which has an accessory pathway between the atria and the ventricles. Reconstruction of source current distribution in a plane below the chest surface was performed using minimum norm estimation (MNE) algorithm and truncated singular value decomposition (SVD), In the simulation, we confirmed that the current distributions. which were computed for the test dipoles, represented well the essential feature of the test current configurations, In the current map of WPW syndrome, we observed abnormal currents that would bypass the atrioventricular junction at a delta wave. However, we could not observe such currents any more after the surgery. These results showed that the obtained current distribution using MCG signals is consistent with the electrical activity in a heart and has clinical usefulness.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.4
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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.

• Proceedings of the IEEK Conference
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• 2000.06e
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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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• v.10
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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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• v.5 no.1
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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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.151-160
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• 2005

In this paper, we propose a new fast motion estimation algorithm based on successive elimination algorithm (SEA) which can dramatically reduce heavy complexity of the variable block size motion estimation in H.264 encoder. The proposed method applies the conventional SEA in the hierarchical manner to the seven block modes. That is, the proposed algorithm can remove the unnecessary computation of SAD by means of the process that the previous minimum SAD is compared to a current SAD for each mode which is obtained by accumulating sum norms or SAD of $4\times4$ blocks. As a result, we have tighter bound in the inequality between SAD and sum norm than in the ordinary SEA. If the basic size of the block is smaller than $4\times4$, the bound will become tighter but it also causes to increase computational complexity, specifically addition operations for sum norm. Compared with fast full search algorithm of JM of H.264, our algorithm saves 60 to $70\%$ of computation on average for several image sequences.

• Progress in Superconductivity
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• v.4 no.1
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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.