• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.649-664
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• 2011

Cooperative spectrum sensing (CSS) with decision fusion is considered as a key technology for tackling the challenges caused by fading/shadowing effects and noise uncertainty in spectrum sensing in cognitive radio. However, most existing solutions assume an error-free decision transmission, which is obviously not the case in realistic scenarios. This paper extends the general decision-fusion-based CSS scheme by considering the fading/shadowing effects and noise corruption in the common control channels. With this more practical model, the fusion centre first estimates the local decisions using a binary minimum error probability detector, and then combines them to get the final result. Theoretical analysis and simulation of this CSS scheme are performed over typical channels, which suggest some performance deterioration compared with the pure case that assumes an error-free decision transmission. Furthermore, the fusion strategy optimization in the proposed cooperation model is also investigated using the Bayesian criteria. The numerical results show that the total error rate of noisy CSS is higher than that of the pure case, and the optimal values of fusion parameter in the counting rule under both cases decrease as the local detection threshold increases.

• 한국음향학회지
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• 제23권3호
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• pp.206-213
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• 2004

본 논문에서는 수중에서 빠른 속도로 기동하는 표적 환경에 적합한 조향각 오차 보정기법을 제안한다. 기존의 협대역 조향각 오차 보정기법에서는 다수의 시간 데이터 단편을 이용한 반면, 제안한 기법은 하나의 시간 데이터 단편에서 다수의 주파수 성분들로부터 모드 공분산행렬을 구성하고, 이를 이용하여 얻어진 광대역 MVDR (Minimum Variance Distortionless Response) 빔출력을 최대화시키는 조향각 오차를 추정함으로써 짧은 관측시간 내에 정확한 표적의 방위각을 추정할 수 있다. 모의신호와 실제 해상 실험 데이터를 이용하여 제안한 기법의 성능을 기존의 기법과 비교, 분석하였다.

• 한국초전도ㆍ저온공학회논문지
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• 제17권3호
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• pp.28-32
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• 2015

Nowadays the magnetic field mapping is widely used in the design and analysis of the NMR/MRI magnet system, and the accuracy of mapping result has become more and more important. There are several factors affecting the accuracy of the mapping such as the mapping method, the precision of the sensor, the position of the measurement points, the calculation accuracy, and so on. In this paper the error due to the misalignment of the measurement points was discussed. The magnetic field in the central volume was mapped using an indirect method in an MRI magnet system and the magnetic field was fitted to a polynomial. Considering the misalignment between the original measurement points and the practical measurement points, there must be some errors in the mapping calculation and we called it positioning error. Several comparisons of the positioning error have been presented through the theoretical estimates and the exact magnetic field values. Finally, the allowable positioning errors were suggested to guarantee the accuracy of the magnetic field mapping within a certain degree for an example case.

• 한국해양공학회지
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• 제31권1호
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• pp.28-35
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• 2017

This paper introduces a GPS-aided dead reckoning algorithm that asymptotically estimates the heading bias error of a magnetic compass based on geodetic north, improves the position error accumulated by dead reckoning, and helps the estimated position of an AUV to represent a position in the NED coordinate system, by receiving GPS position information when surfaced. Based on the results of a simulation, the locational error was bounded with a modest distance, after estimating the AUV position and heading bias error of the magnetic compass when surfaced. In other words, it was verified that proposed algorithm improves the position error in the NED coordinate system.

• 한국멀티미디어학회논문지
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• 제14권8호
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• pp.1000-1009
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• 2011

영상 보간법은 영상의 크기변환에서 할당되지 못한 화소에 대한 값을 추정하는 기술로써, 보간된 결과 영상에서 나타나는 화질 열화 현상을 최소화하면서도 낮은 계산복잡도를 가지는 것이 필요하다. 본 논문에서는 반복적 오차 제거를 이용한 영상 보간법을 제안한다. 제안하는 방법은 5단계로 구성되며, 각각 손실 정보 계산 단계, 손실 정보 추정 단계 손실 정보 적용 단계 오차 계산 단계 오차 적용 단계이다. 실험을 통해서 기존의 방법보다 평균 3.3dB이상 PSNR(peak signal to noise rate)이 향상된 것을 알 수 있었고, 주관적인 화질도 개선된 것을 확인하였으며 계산복잡도가 최소 83% 이상 감소한 것을 측정하였다. 제안한 영상 보간 방법은 영상 복원 및 확대를 위한 다양한 응용 환경에서 유용하게 사용될 수 있다.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1200-1207
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• 2017

Sensors in a smartphone can be used to measure various physical quantities. In this paper, we propose an object localization scheme in a three dimenstional using a smart phone. The proposed scheme estimates the location of an object by observing it from several different points. The direction to the target object and the locations of the observation points are collected at each observation point using the location sensor and the orientation sensor in the smartphone. Based on these observations, the proposed scheme derives three dimensional line of sight vectors and estimates the location of the target object that minimizes the estimation error. We implemented the proposed scheme on an Android smartphone and tested its performance by estimating the height of a building and characteristics of the proposed approach.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.81-92
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• 2007

This paper consider trinomial group testing concerned with classification of N given units into one of k disjoint categories. In this paper, we propose Bayesian inference for estimating individual category proportions using the trinomial group testing model proposed by Bar-Lev et al. (2005). We compared a relative efficience (RE) based on the mean squared error (MSE) of MLE and Bayes estimators with various prior information. The impact of different prior specifications on the estimates is also investigated using selected prior distribution. The impact of different priors on the Bayes estimates is modest when the sample size and group size we large.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.459-462
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• 2003

Selectivity estimation of queries not only provides useful information to the query processing optimization but also may give users with a preview of processing results. In this paper, we investigate the problem of selectivity estimation in the context of a spatial dataset. Although several techniques have been proposed in the literature to estimate spatial query result sizes, most of those techniques still have some drawback in the case that a large amount of memory is required to retain accurate selectivity. To eliminate the drawback of estimation techniques in previous works, we propose a new method called MW Histogram. Our method is based on two techniques: (a) MinSkew partitioning algorithm that processes skewed spatial datasets efficiently (b) Wavelet transformation which compression effect is proven. We evaluate our method via real datasets. With the experimental result, we prove that the MW Histogram has the ability of providing estimates with low relative error and retaining the similar estimates even if memory space is small.

• Communications for Statistical Applications and Methods
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• 제24권3호
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• pp.291-301
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• 2017

It is well known in a small sample that the maximum likelihood (ML) approach for variance components in the general linear model yields estimates that are biased downward. The ML estimate of residual variance tends to be downwardly biased. The underestimation of residual variance, which has implications for the estimation of marginal effects and asymptotic standard error of estimates, seems to be more serious in some limited dependent variable models, as shown by some researchers. An alternative frequentist's approach may be restricted or residual maximum likelihood (REML), which accounts for the loss in degrees of freedom and gives an unbiased estimate of residual variance. In this situation, the REML estimator is derived in a censored regression model. A small sample the REML is shown to provide proper inference on regression coefficients.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.97-108
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• 2020

This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.