• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.789-799
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• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1174-1181
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• 2005

The exact bit error rate(BER) calculation of an UWB-TH PPM multiple access communication system, which is known to be suitable for the fast transmission of massive information data, is introduced. The statistic feature of the multiple access intereference (MAI) of the system is precisely modeled by the characteristic function technique. The concrete expression for the MAI allows the exact expression for BER to be derived. In addition, we propose the approximate expression for the BER which reveals superior accuracy to the expression from the previous Gaussian approximation of the MAI. The validity of the proposed expressions is confirmed from the comparison of proposed results with the results from Monte-Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.57-66
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• 2005

In this paper, we propose a method to evaluate the solutions of the renewal equations related to SPRT for Erlang distribution. In SPRT, the Average Sample Number(ASN) and type I or type II error probabilities are shown in Fredholm type integral equations. The integral equations are generally solved by the approximation method using Gaussian quadrature. For Erlang distribution, it has been known that the exact solutions of the equations exist. We propose the algorithm to solve the equations.

• Journal of the Korean Society of Visualization
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• v.16 no.2
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• pp.23-30
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• 2018

The present study compares flow fields reconstructed by data assimilation method with different combinations of parameters. As a data assimilation method, Vortex-in-Cell-sharp (VIC#), which supplements additional constraints and multigrid approximation to Vortex-in-Cell-plus (VIC+), is used to reconstruct flow fields from scattered particle tracks. Two parameters, standard deviation of Gaussian radial basis function (RBF) and grid spacing, are mainly tested using artificial data sets which contain few particle tracks. Consequent flow fields are analyzed in terms of flow structure sizes. It is demonstrated that sizes of the flow structures are proportional to an actual scale of the standard deviation of RBF. It implies that a combination of larger grid spacing and smaller standard deviation which preserves the actual standard deviation is able to save computational resources in case of a low track density. In addition, a simple comparison using an experimental data filled with dense particle tracks is conducted.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.253-271
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• 2017

In this paper, considering that perfect channel state information (CSI) is hard to achieve in practice, the downlink capacity of distributed antenna systems (DAS) with imperfect CSI and multiple receive antennas is investigated over composite Rayleigh fading channel. According to the performance analysis, using the numerical calculation, the probability density function (PDF) of the effective output SNR is derived. With this PDF, accurate closed-form expressions of ergodic capacity and outage probability of DAS with imperfect CSI are, respectively, obtained, and they include the ones under perfect CSI as special cases. Besides, the outage capacity of DAS in the presence of imperfect CSI is also derived, and a Newton's method based practical iterative algorithm is proposed to find the accurate outage capacity. By utilizing the Gaussian distribution approximation, another approximate closed-form expression of outage capacity is also derived, and it may simplify the calculation of accurate outage capacity. These theoretical expressions can provide good performance evaluation for downlink DAS for both perfect and imperfect CSI. Simulation results verify the effectiveness of the theoretical analysis, and the system capacity can be improved by increasing the receive antennas, and decreasing the estimation error or path loss. Moreover, the system can tolerate the estimation error variance up to about 0.01 with a slight degradation in the capacity.

• Korea-Australia Rheology Journal
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• v.18 no.4
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• pp.199-207
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• 2006

Measurements by Luap et al. (2005) of elongational viscosity and birefringence of two nearly monodisperse polystyrene melts with molar masses $M_{w}$ of $206,000g{\cdot}mol^{-1}$ (PS206k) and $465,000g{\cdot}mol^{-1}$ (PS465k) respectively are reconsidered. At higher elongational stresses, the samples showed clearly deviations from the stress optical rule (SOR). The elongational viscosity data of both melts can be modeled quantitatively by the MSF model of Wagner et al. (2005), which is based on the assumption of a strain-dependent tube diameter and the interchain pressure term of Marrucci and Ianniruberto (2004). The only nonlinear parameter of the model, the tube diameter relaxation time, scales with $M_{w}^{2}$. In order to get agreement with the birefringence data, finite chain extensibility effects are taken into account by use of the $Pad\'{e}$ approximation of the inverse Langevin function, and the interchain pressure term is modified accordingly. Due to a selfregulating limitation of chain stretch by the FENE interchain pressure term, the transient elongational viscosity shows a small dependence on finite extensibility only, while the predicted steady-state elongational viscosity is not affected by non-Gaussian effects in agreement with experimental evidence. However, deviations from the SOR are described quantitatively by the MSF model by taking into account finite chain extensibility, and within the experimental window investigated, deviations from the SOR are predicted to be strain rate, temperature, and molar mass independent for the two nearly monodisperse polystyrene melts in good agreement with experimental data.

• Journal of Communications and Networks
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• v.17 no.3
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• pp.231-240
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• 2015

To facilitate the base station planning in high speed railway communication systems, it is necessary to consider the functional relationships between the base station transmit power and space parameters such as train velocity and cell radius. Since these functions are able to present some inherent system properties determined by its spatial topology, they will be referred to as the power-space functions in this paper. In light of the fact that the line-of-sight path persists the most power of the received signal of each passing train, this paper considers the average transmission rate and bounds on power-space functions based on the additive white Gaussian noise channel (AWGN) model. As shown by Monte Carlo simulations, using AWGN channel instead of Rician channel introduces very small approximation errors, but a tractable mathematical framework and insightful results. Particularly, lower bounds and upper bounds on the average transmission rate, as well as transmit power as functions of train velocity and cell radius are presented in this paper. It is also proved that to maintain a fixed amount of service or a fixed average transmission rate, the transmit power of a base station needs to be increased exponentially, if the train velocity or cell radius is increased, respectively.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.1
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• pp.1-8
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• 2005

Multicarrier code division multiple access(MC-CDMA) Is a scheme that combines multicarrier modulation with CDMA. It offers robustness to frequency selective fading and can support higher rate data transmission with higher spectral efficiency. The objective of this article to proposed a new asynchronous ME-CDMA system to implement multiple data rate communications. It can be accomplished by changing the number of parallel branch(.p). For the analysis of average BER performance, numerical method and computer simulation were used. After MAI power of received signal calculated, the average BER can be acriuired using Gaussian approximation to MAI. We also compare the system performance with that of a single rate MC-CDMA system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.216-225
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• 2007

This paper presents bit splitting methods to apply multilevel modulation to iterative codes such as turbo code, low density parity check code and turbo product code. Log-likelihood ratio method splits multilevel symbols to bits using the received in-phase and quadrature component based on Gaussian approximation. However it is too complicate to calculate and implement hardware due to exponential and log calculation. therefore this paper presents Euclidean, MAX and Sector method to reduce the high complexity of LLR method. We propose optimal bit splitting method for three iterative codes.

• ETRI Journal
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• v.27 no.6
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• pp.747-758
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• 2005

The problem of selection among competing models has been a fundamental issue in statistical data analysis. Good fits to data can be misleading since they can result from properties of the model that have nothing to do with it being a close approximation to the source distribution of interest (for example, overfitting). In this study we focus on the preference among models from a family of polynomial regressors. Three decades of research has spawned a number of plausible techniques for the selection of models, namely, Akaike's Finite Prediction Error (FPE) and Information Criterion (AIC), Schwartz's criterion (SCH), Generalized Cross Validation (GCV), Wallace's Minimum Message Length (MML), Minimum Description Length (MDL), and Vapnik's Structural Risk Minimization (SRM). The fundamental similarity between all these principles is their attempt to define an appropriate balance between the complexity of models and their ability to explain the data. This paper presents an empirical study of the above principles in the context of model selection, where the models under consideration are univariate polynomials. The paper includes a detailed empirical evaluation of the model selection methods on six target functions, with varying sample sizes and added Gaussian noise. The results from the study appear to provide strong evidence in support of the MML- and SRM- based methods over the other standard approaches (FPE, AIC, SCH and GCV).