• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.191-199
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• 2006

In this paper, we propose a method to implement a predistorter of the $rho$-th order inverse filter structure to prevent signal distortion and spectral re-growth due to the high PAPR (peak-to-average ratio) of the OFDM signals and the non-linearity of high-power amplifiers. We model the memory-less non-linearity of the high-power amplifier with a polynomial model and utilize the inverse of the model, the $rho$-th order inverse filter, for the predistorter. Once the non-linearity is modeled with a polynomial, since we can determine the $rho$-th order inverse filter only with the coefficients of the polynomial, large memory is not required. To update the coefficients of the non-linear high-power amplifier model, we can use LMS or RLS algorithms. The convergence speed is high since the number of coefficients is small, and the computation is simple since manipulation of complex numbers is not necessary.

• Journal of IKEEE
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• v.24 no.3
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• pp.766-776
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• 2020

Recently, as interest in machine learning (ML) has increased and research using ML has become active, it is becoming more important to find an optimal hyperparameter combination for various ML models. In this paper, among various hyperparameters, we focused on ML optimizers, and measured and compared the performance of major optimizers using various datasets. In particular, we compared the performance of nine optimizers ranging from SGD, which is the most basic, to Momentum, NAG, AdaGrad, RMSProp, AdaDelta, Adam, AdaMax, and Nadam, using the MNIST, CIFAR-10, IRIS, TITANIC, and Boston Housing Price datasets. Experimental results showed that when Adam or Nadam was used, the loss of various ML models decreased most rapidly and their F1 score was also increased. Meanwhile, AdaMax showed a lot of instability during training and AdaDelta showed slower convergence speed and lower performance than other optimizers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.403-413
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• 2009

We compare three predistortion methods to prevent signal distortion and spectral re-growth due to the high PAPR (peak-to-average ratio) of OFDM signal and the non-linearity of high-power amplifiers. The three predistortion methods are pth order inverse, indirect learning architecture and look up table. The pth order inverse and indirect learning architecture methods requires less memory and has a fast convergence because these methods use a polynomial model that has a small number of coefficients. Nevertheless the convergence is fast due to the small number of coefficients and the simple computation that excludes manipulation of complex numbers by separate compensation for the magnitude and phase. The look up table method is easy to implement due to simple computation but has the disadvantage that large memory is required. Computer simulation result reveals that indirect learning architecture shows the best performance though the gain is less than 1 dB at $BER\;=\;10^{-4}$ for 64-QAM. The three predistorters are adaptive to the amplifier aging and environmental changes, and can be selected to the requirements for implementation.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.33-40
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• 1998

This paper presents an Modified Orthogonal Neural Network(MONN), new modified model of Orthogonal Neural Network(0NN) based on orthogonal functions, and applies it to nonlinear system approximator. ONN proposed by Yang and Tseng, doesn't have the problems of traditional multilayer feedforward neural networks such as the determination of initial weights and the numbers of layers and processing elements. And tranining of ONN converges rapidly. But ONN cannot adapt its orthogonal functions to a given system. The accuracy of ONN, in terms of the minimal possible deviation between system and approximator, is essentially dependent on the choice of basic orthogonal functions. In order to improve ability and effectiveness of approximate nonlinear systems, MONN has an input transformation layer to adapt its basic orthogonal functions to a given nonlinear system. The results show that MONN has the excellent performance of approximate nonlinear systems and the input transfnrmation makes the ability of MONN better than one of ONN.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.416-416
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• 2012

유기물을 기반으로 하는 유기발광소자, 유기메모리 및 유기 태양전지 등과 같은 차세대 전자소자는 기존의 무기물 기반의 소자에 비해 가격이 싸고 제작방법이 간단하며 휘어지게 만들 수 있다는 장점을 갖기 때문에 많은 관심을 받고 있다. 유기물을 기반으로 한 전자 소자의 효율을 향상시키기 위해서는 유기물질이 갖는 고유의 물리적 특성에 관한 연구가 중요하다. 특히, 유기물 내에서의 전하 전송 메카니즘을 이해하기 위해 유기물의 전자 이동도에 대한 연구가 중요하나, 아직까지 유기물질을 기반으로 한 전자 소자의 전자 이동도에 대한 이론적인 연구가 비교적 적다. 본 연구에서는 유기물 내에서의 트랩 분포 변화에 따른 전자 이동도를 몬테카를로 방법을 이용하여 계산하였다. 시뮬레이션을 위한 기본 구조로 소자의 길이는 30-300 사이트로 하였으며, 이웃한 사이트간 거리는 $3{\acute{\AA}}$로 결정하였다. 유기물 내에 존재하는 트랩의 분포는 가우시안 분포로 가정하였고, 트랩의 분산도와 트랩 총량을 변화시켜 계산하였다. 이웃한 트랩간의 천이 확률을 Miller and Abrahams 식을 이용하여 계산하고, 트랩간의 천이시간을 랜덤 변수로 결정하였고, 이들을 통계적으로 처리하여 유기물 내에서의 전자 이동도를 계산하였다. 시뮬레이션 결과는 유기물의 트랩분포가 일정할 경우 전자 이동도는 전계가 증가함에 따라 일정하게 증가하다가 일정 전계에서 포화된 후 다시 감소한다. 초기의 전계 영역에서는 전계의 증가에 따라 유기물 내 트랩간의 천이 확률이 증가하기 때문에 전자 이동도가 증가한다. 하지만, 일정 전계 이상에서는 전자의 이동 속도가 거의 변하지 않기 때문에, 전계의 증가에 따라 전자 이동도는 오히려 줄어들게 된다. 트랩의 분산도가 증가함에 따라 낮은 전계 영역에서는 전자 이동도가 작고, 전계가 증가할수록 분산도와 상관없이 전자 이동도가 비슷한 값으로 수렴한다. 트랩의 분산도가 30 meV로 작을 경우에 일정 온도 이상에서의 전자 이동도는 포화되어 일정한 값으로 유지한다. 유기물 내에 존재하는 트랩 분포에 따라 온도의 변화가 전자 이동도에 미치는 영향이 달라짐을 알 수 있다. 이러한 결과는 유기물질을 기반으로 한 전자소자에서의 전하 전송 메카니즘을 이해하고 소자의 제작 및 특성 향상에 도움이 된다고 생각한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.291-297
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• 2004

In this paper, a new structure for the AEC(Acoustic Echo Canceller) is proposed in which echo signal components that can be created in mobile communications is effectively eliminated. Block Data Flow Architecture is a parallel architecture that achieves high performance, high efficiency, high throughput, and almost linear speed up. The proposed architecture employs AEC and is implemented using the TMS320C6711 for real-time applications. The proposed AEC shows improved performance by eliminating echoes at 55ms delay path. Since the proposed AEC can also be implemented in Firmware, it is believed to effectively work on various types of echoes if it is applied on CDMA mobile devices. The TMS320C6711 shows much better performance comparing to previous DSPs. For experimental verifications, filtering operation using adaptive algorithm is performed on TMS320C6711 board and error signals resulted from computations are monitored on PC, and then the performance of the implemented AEC is verified through ERLE computation. According the results of simulation, good characteristic of 100dB are shown after 500 sampling data.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.9
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• pp.37-43
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• 2010

An Interference Cancellation Wireless Repeater transmitts directly amplified the RF signal input to extend the coverage of the base station. Such a repeater inevitably suffers from the feedback interferences due to the environment and the adaptive Interference Cancelling System(ICS) is necessary. In this paper, the Variable Stepsize Complex Sign -Sign(VSCSS) LMS algorithm for ICS is presented. The algorithm can be implemented without multiplication/division arithmetic operation so that the required logic resources can be dramatically reduced in FPGA implementation. The performance of the proposed algorithm was analyzed in comparison with CSS-LMS algorithm and the learning curves obtained from simulation showed an excellent agreement with the theorical prediction. The simulation result with ICS in fading feedback channel environment showed the performance of the proposed algorithm is competible with NLMS algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1998-2009
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• 1998

An effective algorithm for tracking rigid or non-rigid moving object(s) which segments local moving parts from image sequence in the presence of backgraound motion by camera movenment, predicts the direction of it, and tracks the object is proposed. It requires no camera calibration and no knowledge of the installed position of camera. In order to segment the moving object, feature points configuring the shape of moving object are firstly selected, feature flow field composed of motion vectors of the feature points is computed, and moving object(s) is (are) segmented by clustering the feature flow field in the multi-dimensional feature space. Also, we propose IRMAS, an efficient algorithm that finds the convex hull in order to cinstruct the shape of moving object(s) from clustered feature points. And, for the purpose of robjst tracking the objects whose movement characteristics bring about the abrupt change of moving trajectory, an improved order adaptive lattice structured linear predictor is used.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.560-570
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• 2013

In this paper, we propose transceiver design strategies for the two-cell multiple-input multiple-output (MIMO) interfering broadcast channel where inter-cell interference (ICI) exists in addition to inter-user interference (IUI). We first formulate the generalized zero-forcing interference alignment (ZF-IA) method based on the alignment of IUI and ICI in multi-dimensional subspace. We then devise a minimum weighted-mean-square-error (WMSE) method based on "regularizing" the precoders and decoders of the generalized ZF-IA scheme. In contrast to the existing weighted-sum-rate-maximizing transceiver, our method does not require an iterative calculation of the optimal weights. Because of this, the proposed scheme, while not designed specially to maximize the sum-rate, is computationally efficient and achieves a faster convergence compared to the known weighed-sum-rate maximizing scheme. Through analysis and simulation, we show the effectiveness of the proposed regularized ZF-IA scheme.

• Journal of Korea Port Economic Association
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• v.26 no.2
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• pp.49-57
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• 2010

This paper examines the relationship between port import from China and macroeconomic variables such as international financial crisis, exchange rate, and industrial production during the period 2000-2009. I employ GPH cointegration methodology since the model must be stationary to avoid the spurious results. The empirical results show that our model is stationary as well as mean-reverting. This paper also applies impulse-response functions to get additional information regarding the responses of the port import to the shocks economic variables such as financial crisis, exchange rate, and industrial production. The results show that the response of port import to exchange rate and financial crisis declines at the first and dies out slowly.