• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.49-55
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• 2020

Information theoretic learning (ITL) methods based on random symbols (RS) use a set of random symbols generated according to a target distribution and are designed nonparametrically to minimize the cost function of the Euclidian distance between the target distribution and the input distribution. One drawback of the learning method is that it can not utilize the input power statistics by employing a constant stepsize for updating the algorithm. In this paper, it is revealed that firstly, information potential input (IPI) plays a role of input in the cost function-derivative related with information potential output (IPO) and secondly, input itself does in the derivative related with information potential error (IPE). Based on these observations, it is proposed to normalize the step-size with the statistically varying power of the two different inputs, IPI and input itself. The proposed algorithm in an communication environment of impulsive noise and multipath fading shows that the performance of mean squared error (MSE) is lower by 4dB, and convergence speed is 2 times faster than the conventional methods without step-size normalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.232-239
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• 1992

In this paper, an analytical expression of the excess MSE of ITLMS(Individual Tap LMS) which results from the random fluctuation of the distance between the actual and optimal coefficients due to noisy gradient estimates, is derived. The expression reveals that the excess MSE of the ITLMS algorithm is smaller that that of the LMS algorithm. The performance of the algorithm from the computer simulation for a fading time-dispersive channel verifies the theoretical results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.343-347
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• 2012

Non-linear equalization techniques using decision feedback structure are highly demanded for cancellation of intersymbol interferences occurred in severe channel environments. In this paper decision feedback structure is applied to the linear blind equalizer algorithm that is based on information theoretic learning and a randomly generated symbol set. At the decision feedback equalizer (DFE) the random symbols are generated to have the same probability density function (PDF) as that of the transmitted symbols. By minimizing difference between the PDF of blind DFE output and that of randomly generated symbols, the proposed DFE algorithm produces equalized output signal. From the simulation results, the proposed method has shown enhanced convergence and error performance compared to its linear counterpart.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.53-68
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• 2008

We study on the practical privacy-preserving techniques by matrix-based randomization approach. We clearly examine the relationship between the two parameters associated with the measure of privacy breach and the condition number of matrix in order to achieve the optimal transition matrix. We propose a simple formula for efficiently calculating the inverse of transition matrix which are needed in the re-construction process of random substitution algorithm, and deduce some useful connections among standard error and another parameters by obtaining condition numbers according to norms of matrix and the expectation and variance of the transformed data. Moreover we give some experimental results about our theoretical expressions by implementing random substitution algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.8
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• pp.572-579
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• 2003

By comparing the measured optical reflection spectra with calculated one by the transfer-matrix method (TMM) in epitaxial wafers for vertical-cavity surface-emitting lasers (VCSELs), we have estimated the systematic thickness errors in a simple and nondestructive way. The experimentally confirmed technique is based on the finding that the shape of the reflection spectra depends mainly on a newly defined single parameter, the effective error in the n-mirror layers, and the thickness error in the active cavity simply shifts the Fabry-Perot resonance wavelength. Also shown is that the proposed method is reliable when the relative standard deviation of the random thickness errors is less than 0.005. Because reflection spectra are routinely measured, we can easily estimate the thickness errors nondestructively with high spatial resolution.

• Journal of radiological science and technology
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• v.40 no.1
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• pp.63-70
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• 2017

The purpose of this study was compare to the patient setup deviation of two different type thermoplastic immobilization masks for glottis cancer in the intensity-modulated radiation therapy (IMRT). A total of 16 glottis cancer cases were divided into two groups based on applied mask type: standard or alternative group. The mean error (M), three-dimensional setup displacement error (3D-error), systematic error (${\Sigma}$), random error (${\sigma}$) were calculated for each group, and also analyzed setup margin (mm). The 3D-errors were $5.2{\pm}1.3mm$ and $5.9{\pm}0.7mm$ for the standard and alternative groups, respectively; the alternative group was 13.6% higher than the standard group. The systematic errors in the roll angle and the x, y, z directions were $0.8^{\circ}$, 1.7 mm, 1.0 mm, and 1.5 mm in the alternative group and $0.8^{\circ}$, 1.1 mm, 1.8 mm, and 2.0 mm in the alternative group. The random errors in the x, y, z directions were 10.9%, 1.7%, and 23.1% lower in the alternative group than in the standard group. However, absolute rotational angle (i.e., roll) in the alternative group was 12.4% higher than in the standard group. For calculated setup margin, the alternative group in x direction was 31.8% lower than in standard group. In contrast, the y and z direction were 52.6% and 21.6% higher than in the standard group. Although using a modified thermoplastic immobilization mask could be affect patient setup deviation in terms of numerical results, various point of view for an immobilization masks has need to research in terms of clinic issue.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.359-362
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• 2000

ANC시스템에 있어서 현재 많이 이용되고있는 Filtered-X LMS 알고리즘에서 2차 음원과 제어점간의 임펄스응답은, 미리 동정하여 사용하는 것이 일반적이지만, 2차 음원과 제어점간의 전달특성이 이후에 변화할 경우, 실제의 전달함수와 적응에 이용한 전달함수간에 모델링 오차가 발생하게된다. 이 모델링 오차에 의하여 알고리즘은 오동작을 일으키고, 시스템은 불안정하게 되기도 한다. 따라서, 본 연구에서는 참조신호가 랜덤신호일 경우에 발생하는 모델링 오차와 Filtered-X LMS 알고리즘의 오동작에 관한 이론식을 도출하고, 시뮬레이션을 통하여 이를 입증하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.111-116
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• 2018

This paper introduces the concept of a random universal hash function to amplify security in a quantum key distribution system. It seems to provide security amplification using the relationship between quantum error correction and security. In addition, the approach in terms of security amplification shows that phase error correction offers better security. We explain how the universal hash function enhances security using the BB84 protocol, which is a typical example of QKD(Quantum Key Distribution). Finally, we show that the BB84 protocol using random privacy amplification is safe at higher key rates than Mayers' performance at the same error rate.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.5
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• pp.335-341
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• 2013

The variation of systematic bias errors in the wind tunnel testing has been studied. A Design of Experiments(DOE) approach to an experimental study of fuselage drag and stability characteristics of a helicopter configuration was applied. When forces and moments measured in one time block differ significantly from measurements made in another time block under assumption that sample observations can be expected to yield same results within permissible measuring errors. The practical implication of this paper is that the systematic error can not be assumed not to exist. The those error reduction could be achieved through the process of randomization, blocking, and replication of the data points.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.33-39
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• 2010

Correntropy is a generalized correlation function that contains higher order moments of the probability density function (PDF) than the conventional moment expansions. The criterion maximizing cross-correntropy (MCC) of two different random variables has yielded superior performance particularly in nonlinear, non-Gaussian signal processing comparing to mean squared error criterion. In this paper we propose a new blind equalization algorithm based on cross-correntropy criterion which uses, as two variables, equalizer output PDF and Parzen PDF estimate of a set of randomly generated symbols that complies with the transmitted symbol PDF. The performance of the proposed algorithm based on MCC is compared with the Euclidian distance minimization.