• Steel and Composite Structures
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• v.20 no.5
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• pp.1119-1131
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• 2016

As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen's nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.613-616
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• 2008

In this paper, a fine residual frequency offset estimation scheme is proposed for multiband orthogonal frequency division multiplexing ultra-wideband (MB-OFDM UWB) systems. The basic idea of our approach is based on the fact that two adjacent OFDM symbols carry the identical information in the MB-OFDM UWB system, thus removing the need of pilot symbols. The mean square error of the synchronization scheme is evaluated and simulation results are used to verify the effectiveness of the proposed estimator. When compared to the pilot-aided conventional estimator, the proposed estimator has a lower estimation error.

• Journal of electromagnetic engineering and science
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• v.8 no.4
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• pp.139-143
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• 2008

In this paper, a new scheme to calculate the weighting factor of the 2-D isotropic-dispersion finite difference time domain(ID-FDTD) is proposed. The weighting factor in [1] was formulated in free space, so that it may not be optimal in dielectric media. Therefore, the weighting factor was reformulated by considering the material properties and using the least mean square method. As a result, a minimum numerical dispersion error for any dielectric media is guaranteed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1313-1316
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• 1993

This paper presents a fuzzy system that estimates the optimal bit allocation matrices for the spatially active subimage classes of adaptive transform image coding in noisy channels. Transform image coding is good for image data compression but it requires a transmission error protection scheme to maintain the performance since the channel noise degrades its performance. The fuzzy system provides a simple way of estimating the bit allocation matrices from the optimal bit map computed by the method of minimizing the mean square error between the transform coefficients of the original and the reconstructed images.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.667-677
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• 2007

In this paper, we propose a method for estimating the mean of a population which has a linear trend, when both n, the sample size, and k, the reciprocal of the sampling fraction, are odd numbers. The proposed method, not having the drawbacks of centered systematic sampling, centered modified sampling and centered balanced sampling, consists of selecting a sample by balanced systematic sampling and estimating the population mean by using interpolation. We compare the efficiency of the proposed method and existing methods under the criterion of the expected mean square error based on the infinite superpopulation model.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1309-1317
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• 2013

There are various parameter estimation methods for the generalized exponential distribution under progressive type I interval censoring. Chen and Lio (2010) studied the parameter estimation method by the maximum likelihood estimation method, mid-point approximation method, expectation maximization algorithm and methods of moments. Among those, mid-point approximation method has the smallest mean square error in the generalized exponential distribution under progressive type I interval censoring. However, this method is difficult to derive closed form of solution for the parameter estimation using by maximum likelihood estimation method. In this paper, we propose two type of approximate maximum likelihood estimate to solve that problem. The simulation results show the obtained estimators have good performance in the sense of the mean square error. And proposed method derive closed form of solution for the parameter estimation from the generalized exponential distribution under progressive type I interval censoring.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.163-168
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• 2009

In this paper, We proposed the efficient method of cleaning impulse noise using mean shift segmentation. This method do its job for the pixel which is identified as impulse noise using mean shift segmentation instead of all pixel of image by the existing method. we found that the quality of image is improved by measuring the sum of square error in result image and impulse noise is cleaned efficiently by doing experiment.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.63-75
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• 2010

In this paper, the equalizer techniques that is able to adopt the digital on-channel repeater for 8VSB-based DTV system has been analyzed and we propose an effective equalizer structure which can reduce the error propagation phenomenon by the feedback signal and improve the receiver performance at the same time. In order to confirm the effective cancellation of the feedback signal, the multi-level Correlation LMS scheme is proposed through the analysis of conventional basic LMS based DFE and Correlation LMS algorithm and as compared with the conventional method, we can confirm the reduction of error propagation. When performing the computer simulation, as the Brazil channel model which is very popular for DTV broadcasting system is adopted, the result is drawn by comparing and analysing the equalizer algorithm. We have examine the symbol error rate which is in the range of 15~25dB of operation receipt SNR and MSE(Mean Square Error) in the DTV broadcasting system. As a result of comparing with the existing method, the signal-noise ratio which is necessary for maintain the bit error correction ability that the means of proposal is same is reduced by about 2~5dB, and in the rate of convergence through the MSE, we found the reduction of needed time.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.176-185
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• 2008

In this paper, new filtering method for sensor registration is provided to estimate and correct error of registration parameters in multiple sensor environments. Sensor registration is based on filtering method to estimate registration parameters in multiple sensor environments. Accuracy of sensor registration can increase performance of data fusion method selected. Due to various error sources, the sensor registration has registration errors recognized as multiple objects even though multiple sensors are tracking one object. In order to estimate the error parameter, new nonlinear information filtering method is developed using minimum mean square error estimation. Instead of linearization of nonlinear function like an extended Kalman filter, information estimation through unscented prediction is used. The proposed method enables to reduce estimation error without a computation of the Jacobian matrix in case that measurement dimension is large. A computer simulation is carried out to evaluate the proposed filtering method with an extended Kalman filter.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.43-46
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• 1998

Many of the active noise control system utilize a form of the least mean square(LMS) algorithm. This paper discusses the dependence of the convergence rate on the acoustic error path in the popular algorithm which is conventional "filtered-x LMS" and introduces new algorithm "constrained filtered-x LMS". The proposed method increase the convergence region regardless of the time-delay in the acoustic error path. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the control process become stationary. Advantages of constrained filtered-x LMS algorithm is illustrated by convergence analysis in the mean sense.