• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.96-101
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• 2011

It is well known that the Capon algorithm offers better resolution compared to that of the FM (Fourier method) algorithm by minimizing the total output power while maintaining a constant gain in the look direction. Unfortunately, the DoA (Direction of Arrival) estimation performance of the Capon algorithm is drastically degraded when the SNR of received signal is low and thus, it cannot distinguish among signal sources which have similar incidence angles. In this paper, we propose a novel scheme enhancing the resolution of the Capon algorithm by ing all rows except the first row of an inverse covariance matrix.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.984-996
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• 2007

This paper presents techniques of 2-D scattering center extraction and 2-B ISAR(Inverse SAR) image formation for scattering wave which is scattered by a target. In general, 2-D IFFT is widely used to obtain 2-D scattering center and ISAR image of targets. But, this method has drawbacks, that is poor in a resolution aspect. To overcome these shortcomings with the FT(Fourier Transform)-based method, various techniques of high resolution signal processing were developed. In this paper, algorithms of 2-D scattering center extraction and ISAR image formation such as 2-D MEMP(Matrix Enhancement and Matrix Pencil), 2-D ESPRIT(Estimation of Signal Parameter via Rotational Invariance Techniques) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and F-18 aircraft to estimate 2-D scattering center and abtain 2-D ISAR image.

• Journal of IKEEE
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• v.18 no.2
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• pp.272-281
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• 2014

In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.103-110
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• 2012

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. Using the inverse of the eigenvalue-weighted eigen spectra, the algorithm detects the DOAs of multiple sources. To apply the algorithm in target signal detection for GSC-based beamforming, we utilize its spectral response for the DOA of the target source in noisy conditions. The performance of the proposed target signal detection method is compared with those of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics (ROC) curves.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.54-59
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• 2005

The cylindrical object are widely used as mechanical parts in the manufacturing process. In order to handling those objects using a robot or an automated machine automatically, the pose of the object must be known. The pose can be described by two rotation angles; one angle about the x axis and the other about the y axis. In the many previous researches these angles were obtained by the computationally intensive algorithm, that is, fitting the data as a polynomial and doing pseudo inverse. So that, this method required high performance microprocessor. In this paper in order to avoid complex computation, a new method based on a genetic algorithm is proposed and analyzed through a series of simulations. This algorithm utilized the geometry of the cylindrical shape. The simulation results show that this method find the pose angles very well In most cases, but the computation time is randomly changed because the genetic algorithm is basically one of the random search method.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.65-68
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• 1994

시각자극에 의해 머리표면에서 발생하는 Transient Evoked Potential을 검출하여 Source Tracing Method를 이용하여 뇌의 시각인지영역을 추정하였다. 본 과정에서 TEP검출방식은 average method를 이용하였고, 신경흥분에 대한 물리적 모델로 Single Current Dipole Model을 이용하고, 머리기하에 대한 3중구각모델을 이용하여 Forward Problem을 풀었다. Inverse Problem은 current dipole의 6개의 parameter에 대한 Least Square Error Method를 이용하여 신경흥분의 위치를 추정하였다. 이러한 결과와 생리학적으로 밝혀진 시각경로와의 비교결과 유사성이 확인되었다.

• Journal of KSNVE
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• v.9 no.2
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• pp.377-386
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• 1999

This paper is a study on model method for estimating system inputs from vibration responses, which is one of indirect input identification methods in frequency domain. The method has advantages over direct inverse method especially when points of operational inputs are inaccessible so that artificial excitation forces cannot be applied to obtain frequency response functions of the complete system. Procedures of extended modal model method are proposed and checked by numerical experiment. Mechanisms of error propagation, i.e., how errors in modal parameters such as poles nad mode shape vectors affect estimation of the input forces, are illustrated. Then, in order to counteract the error propagation, discrete modal filter approach is taken in this paper to compute the inversion of modal matrix in which the most serious errors seem to be generated. Further, a Reduced form of Modified Reciprocal Modal Vector(RMRMV) is proposed for estimating multiple inputs. It is shown to have smaller orthogonality error than MRMV.

• Journal of Environmental Science International
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• v.22 no.2
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• pp.151-161
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• 2013

The assessment of personal exposure is a critical component in population-based epidemiologic studies of air pollution. This study was conducted to apply and compare the four exposure estimation methods of individual-level to air pollution concentration in a cohort including 2,283 subjects in Gwangyang, Korea. Individual-level exposure of air pollution were estimated using multiple approaches, including average across all monitors, nearest monitor, and spatial interpolation by inverse distance weighting and kriging. The mean concentrations of $PM_{10}$, $NO_2$, $SO_2$, CO, $O_3$ by four exposure estimation methods were slightly different but not significantly different from each other. Cross-validation showed that kriging was more accurate than other exposure estimation methods because kriging has probably predicted individual exposure levels equivalent to residential locations after estimating the parameters of a model according to the spatial surface of air pollution concentration. These data support that spatial interpolation methods may provide better estimates than selecting the value from the nearest monitor and averaging across values from all monitors by reflecting spatial attributes of air pollution on personal level.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.113-116
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• 1994

Estimation of the evoked potential using the iterated bispectrum and cross-correlation (IBC) has been tried for both simulation and real clinical data. Conventional time average (TA) method suffers from synchronization error when the latency time of the evoked potential is random, which results in poor SNR distortion in the estimation of EP waveform. Instead of EP signal average in time domain, bispectrum is used which is insensitive to time delay. The EP signal is recovered by the inverse transform of the Fourier amplitude and phase obtained from the bispectrum. The distribution of the latency time is calculated using cross-correlation between EP signal estimated by the bispectrum and the acquired signal. For the simulation. EEG noise was added to the known EP signal and the EP signal was estimated by both the conventional technique and bispectrum technique. The proposed bispectrum technique estimates EP signal more accurately than the conventional technique with respect to the maximum amplitude of a signal, full width at half maximum(FWHM). signal-to-noise-ratio, and the position of maximum peak. When applied to the real visual evoked potential(VEP) signal. bispectrum technique was able to estimate EP signal more distinctively. The distribution of the latency time may play an important role in medical diagonosis.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.59-74
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• 2004

The paper considers the Bayesian interval estimation for the common mean of several normal populations. A Bayesian procedure is proposed based on the idea of matching asymptotically the coverage probabilities of Bayesian credible intervals with their frequentist counterparts. Several frequentist procedures based on pivots and P-values are introduced and compared with Bayesian procedure through simulation study. Both simulation results demonstrate that the Bayesian procedure performs as well or better than any available frequentist procedure even from a frequentist perspective.