• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2106-2115
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• 1994

As a pre processing for an edge detection process. edge preserving smoothing algorithm is proposed. For this purpose we used the interpolation method using B-spline basis function and scaling of digital images. By approximation of continuous function from descrete data using B-spline basis function. undetermined data between two sample can be computed. so that they smooth the surfaces of objects. Some edges having mainly low frequency components are detected using down scaling of the images. Edge maps from proposed pre processed images are hardly affected by the varying space constants($\sigma$) and threshold values used in detecting zero-crossing.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.12
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• pp.56-65
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• 2001

This paper proposes an algorithm for the capacitance extraction of general 3-dimensional conductors in an ideal uniform dielectric that uses a high-order quadrature approximation method combined with the typical first-order collocation method to enhance the accuracy and adopts an efficient matrix-vector product algorithm for the model-order reduction to achieve efficiency. The proposed method enhances the accuracy using the quadrature method for interconnects containing corners and vias that concentrate the charge density. It also achieves the efficiency by reducing the model order using the fact that large parts of system matrices are of numerically low rank. This technique combines an SVD-based algorithm for the compression of rank-deficient matrices and Gram-Schmidt algorithm of a Krylov-subspace iterative technique for the rapid multiplication of matrices. It is shown through the performance evaluation procedure that the combination of these two techniques leads to a more efficient algorithm than Gaussian elimination or other standard iterative schemes within a given error tolerance.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.184-191
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• 2015

In this paper, a normal mode reverberation model for a range-independent environment of shallow water is proposed to calculate the reverberation level in the low-frequency range. Normal mode is used to calculate the acoustic energy propagating from the source to the scattering area and from the scattering area to the receiver. Each mode is decomposed into up and down going waves to consider scattering strength at the scattering area. The scattering functional form combines Lambert's law with a Gaussian-like term near the specular direction based on Kirchhoff approximation considering bottom condition. For verification of the suggested model, the result is relatively compared to several solutions of the problem XI and XV in the Reverberation Modeling Workshop I sponsored by the US Office of Naval Research.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.847-851
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• 2004

In the original mixture density network(MDN), which was introduced by Bishop and Nabney, the parameters of the conditional probability density function are represented by the output vector of a single multi-layer perceptron. Among the recent modification of the MDNs, there is the so-called modified mixture density network, in which each of the priors, conditional means, and covariances is represented via an independent multi-layer perceptron. In this paper, we consider a further simplification of the modified MDN, in which the conditional means are linear with respect to the input variable together with the development of the MATLAB program for the simplification. In this paper, we first briefly review the original mixture density network, then we also review the modified mixture density network in which independent multi-layer perceptrons play an important role in the learning for the parameters of the conditional probability, and finally present a further modification so that the conditional means are linear in the input. The applicability of the presented method is shown via an illustrative simulation example.

• Proceedings of the KIEE Conference
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• 1998.07d
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• pp.1252-1254
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• 1998

The characteristics of linear dichroism with temperature were investigated in normally($0^{\circ}$) and $80^{\circ}$-obliquely deposited amorphous $As_{40}Ge_{10}Se_{15}S_{35}$ thin films using low temperature equipment. The saturated dichroism($D_{sat}$) of a $80^{\circ}$-obliquely deposited film shows approximately 6% which is the larger value than 4.2 % of normally($0^{\circ}$) deposited film. The $D_{sat}$ of $80^{\circ}$-deposited film was increased to 25 % at 77 K, which is four times larger than that at room temperature. The $D_{sat}$ decreased with increasing temperature and was completely disappeared at about 335K. This could be explained as the tunneling effect due to the thermal excitation of lone-pair electrons in intimate valence alternation pairs(IVAPs) which are considered to be the origin of anisotropy. The decrease of $D_{sat}$ with increasing temperature from 77K to room temperature satisfied Gaussian approximation with a standard deviation of 158K.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.36-44
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• 2012

We had introduced the backgrounds, history and physical meanings of Jong Nang in "Jeju Jong Nang Channel Code I". In this paper, we introduce practical the root of digital human binary coded Jong Nang communications as the wooden gate in Korea Jeju Island custom. We investigate Jong Nang gatemodels as an approximation of the AWGN model. The objective is to find a deterministic model, which is accessible to capacity analysis. Furthermore, this analysis should provide insights on the capacity of the AWGN model. Motivated by backhaul cooperation in cellular networks where cooperation is among base stations, we term the interference channel with conferencing transmitters. Jong Nang communicationsis normal 3 rafters placed on two vertical stones with three holes to convey the family's whereabouts that is deterministic signal, nowadays it is applied to backhaul in mobile base station and traffic signal.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.12 s.115
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• pp.1164-1171
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• 2006

In this paper, a simple and nonlinear MMSE detector is derived from the conventional linear MMSE detector to improve the system performance in turbo processing MIMO system and a new turbo processing MIMO system with nonlinear MMSE detector and Gaussian approximation is proposed. In turbo coded turbo processing MIMO system, the proposed system of M=N=4 performs about 0.5 dB better than the conventional system and the proposed system of M=N=8 performs about 0.4 dB better than conventional system at 1 % FER. In addition, the average number of outer iterations of proposed system shows lower than that of conventional system. This is caused by the fact that the nonlinear MMSE detector of proposed system decides soft-outputs of coded bits based on the observation of received signals, so that it can reduce the uncertainty region in estimating the coded bits.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.951-957
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• 2005

The bit error probability of UWB Time-Hopping(TH) multiple access communication systems combined with BPSK is calculated with a high accuracy including the multiple user interference(MUI). This paper finds that with some manipulations, the TH-BPSK UWB signal can be modified to the similar form of the DS-CDMA signal. The MUI in the system is explained by the characteristic function technique. Above two descriptions have been bases on the derivation of the exact BER expression of the system. We also propose the approximate expression for the BER, which has enough accuracy compared with the expression from the Gaussian approximation of the MUI. The comparison of the results from the proposed expressions with the simulation results gives the confirmation for the validity and accuracy of the proposed expressions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.4
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• pp.342-353
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• 1997

This paper presents an analytical evaluation of a hybrid direct-sequence/slow frequencyhopped code division multiple-access (DS/SFH-CDMA) system employing noncoherent M-ary frequency shift keying(MFSK) modulation in a multiple Nakagami fading (m) environment. Multipath interference (MPI) and multi-access interference (MAI) is taken into account and the spectral efficiency is calculated for uncoded as well as channel coding systems. Predetection multipath maximal ratio combining (MRC) diversity in conjunction with interleaved channel coding (Hamming(7,4) code, BCH(15, 7) code and RS (7, 4), (15, 9)) code ) is employed for improving the bit error rate (BER) performance. The BER of noncoherent hybrid system is obtained using a Gaussian interference approximation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.399-406
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• 2009

In this study, Polynomial Radial Basis Function Neural Network(pRBFNN) based on Fuzzy Inference System is designed and its parameters such as learning rate, momentum coefficient, and distributed weight (width of RBF) are optimized by means of Particle Swarm Optimization. The proposed model can be expressed as three functional module that consists of condition part, conclusion part, and inference part in the viewpoint of fuzzy rule formed in 'If-then'. In the condition part of pRBFNN as a fuzzy rule, input space is partitioned by defining kernel functions (RBFs). Here, the structure of kernel functions, namely, RBF is generated from HCM clustering algorithm. We use Gaussian type and Inverse multiquadratic type as a RBF. Besides these types of RBF, Conic RBF is also proposed and used as a kernel function. Also, in order to reflect the characteristic of dataset when partitioning input space, we consider the width of RBF defined by standard deviation of dataset. In the conclusion part, the connection weights of pRBFNN are represented as a polynomial which is the extended structure of the general RBF neural network with constant as a connection weights. Finally, the output of model is decided by the fuzzy inference of the inference part of pRBFNN. In order to evaluate the proposed model, nonlinear function with 2 inputs, waster water dataset and gas furnace time series dataset are used and the results of pRBFNN are compared with some previous models. Approximation as well as generalization abilities are discussed with these results.