• Journal of Power Electronics
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• v.16 no.1
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• pp.310-318
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• 2016

This paper presents a new orthogonal signals generator (OSG) with DC Offset rejection for implementing a phase locked loop (PLL) in single-phase grid-connected power systems. An adaptive filter (AF) based on the least mean square (LMS) algorithm is used to constitute the OSG in this study. The DC offset in the measured grid voltage signal can be significantly rejected in the developed OSG technique. This generates two pure orthogonal signals that are free from the DC offset. As a result, the DC offset rejection performance of the presented single-phase phase locked loop (SPLL) can be enhanced. A mathematical model of the developed OSG and the principle of the adaptive filter based SPLL (AF-SPLL) are presented in detail. Finally, simulation and experimental results demonstrate the feasibility of the proposed AF-SPLL.

• Structural Engineering and Mechanics
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• v.36 no.2
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• pp.225-241
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• 2010

In this study, a hybrid search algorithm combining genetic programming with orthogonal least squares (GP/OLS) is utilized to generate prediction models for compressive strength of high performance concrete (HPC) mixes. The GP/OLS models are developed based on a comprehensive database containing 1133 experimental test results obtained from previously published papers. A multiple least squares regression (LSR) analysis is performed to benchmark the GP/OLS models. A subsequent parametric study is carried out to verify the validity of the models. The results indicate that the proposed models are effectively capable of evaluating the compressive strength of HPC mixes. The derived formulas are very simple, straightforward and provide an analysis tool accessible to practicing engineers.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.399-404
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• 2012

Evolutionary algorithms such as genetic algorithm (GA) have been proven their effectiveness when applying to the design of fuzzy models. However, it tends to suffer from computationally expensWive due to the slow convergence speed. In this study, we propose an approach to develop fuzzy models by means of an improved differential evolution (IDE) to overcome this limitation. The improved differential evolution (IDE) is realized by means of an orthogonal approach and differential evolution. With the invoking orthogonal method, the IDE can search the solution space more efficiently. In the design of fuzzy models, we concern two mechanisms, namely structure identification and parameter estimation. The structure identification is supported by the IDE and C-Means while the parameter estimation is realized via IDE and a standard least square error method. Experimental studies demonstrate that the proposed model leads to improved performance. The proposed model is also contrasted with the quality of some fuzzy models already reported in the literature.

• ETRI Journal
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• v.42 no.6
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• pp.815-826
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• 2020

We propose a two-dimensional (2D) scattering-center-extraction (SCE) method using sparse recovery based on the compressive-sensing theory, even with data missing from the received radar cross-section (RCS) dataset. First, using the proposed method, we generate a 2D grid via adaptive discretization that has a considerably smaller size than a fully sampled fine grid. Subsequently, the coarse estimation of 2D scattering centers is performed using both the method of iteratively reweighted least square and a general peak-finding algorithm. Finally, the fine estimation of 2D scattering centers is performed using the orthogonal matching pursuit (OMP) procedure from an adaptively sampled Fourier dictionary. The measured RCS data, as well as simulation data using the point-scatterer model, are used to evaluate the 2D SCE accuracy of the proposed method. The results indicate that the proposed method can achieve higher SCE accuracy for an incomplete RCS dataset with missing data than that achieved by the conventional OMP, basis pursuit, smoothed L0, and existing discrete spectral estimation techniques.

• Journal of Power Electronics
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• v.17 no.1
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• pp.149-160
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• 2017

To improve the performance of sensorless induction motor (IM) drives, an adaptive speed estimation method based on a strong tracking extended Kalman filter with a least-square algorithm (LS-STEKF) for induction motors is proposed in this paper. With this method, a fading factor is introduced into the covariance matrix of the predicted state, which forces the innovation sequence orthogonal to each other and tunes the gain matrix online. In addition, the estimation error is adjusted adaptively and the mutational state is tracked fast. Simultaneously, the fading factor can be continuously self-tuned with the least-square algorithm according to the innovation sequence. The application of the least-square algorithm guarantees that the information in the innovation sequence is extracted as much as possible and as quickly as possible. Therefore, the proposed method improves the model adaptability in terms of actual systems and environmental variations, and reduces the speed estimation error. The correctness and the effectiveness of the proposed method are verified by experimental results.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.277-279
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• 2004

In this paper, we propose an channel estimation method for Multi-Input Multi-Output-Orthogonal frequency Division Multiplexing (MIMO-OFDM). The proposed method estimates uniquely all channel frequency responses needed in space-frequency block coded OFDM systems using "comb-type" pilot symbols. To reduce the computational complexity of the proposed method, least square(LS) and linear minimum mean square error(LMMSE) are used in the frequency-domain. The performance of the proposed approach is evaluated by computer simulation for rayleigh fading channel.

• ETRI Journal
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• v.28 no.6
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• pp.822-825
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• 2006

Based on superimposed training methods, a novel time-varying multipath channel estimation scheme is proposed for orthogonal frequency division multiplexing systems. We first develop a linear least square channel estimator, and meanwhile find the optimal superimposed sequences with respect to the channel estimates' mean square error. Next, a low-rank approximated channel estimator is obtained by using the singular value decomposition. As demonstrated in simulations, the proposed scheme achieves not only better performance but also higher bandwidth efficiency than the conventional pilot-aided approach.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.97-109
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• 2001

This article is devoted to “forgotten” and rarely used technique of matrix analysis, introduced in 60-70th and enhanced by authors. We will study the matrix trace operator and it’s differentiability. This idea generalizes the notion of scalar derivative for matrix computations. The list of the most common derivatives is given at the end of the article. Additionally we point out a close connection of this technique with a least square problem in it’s classical and generalized case.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.11
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• pp.943-950
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• 2013

This paper discusses a harmonic response estimation method on the L$\acute{e}$vy plate with two opposite edges simply supported and the other two edges having free boundary conditions. Since the equation of motion of the plate is not self-adjoint, the modes are not orthogonal to each other on the domain. Noting that the L$\acute{e}$vy plate can be expressed using one term sinusoidal function that is orthogonal to other sinusoidal functions, this paper suggested the calculation method that is equivalent to finding a least square error minimization solution of the finite number of algebraic equations. Example problems subjected to a distributed area loading and a distributed line loading are defined and their solutions are provided. The solutions are compared to those of the commercial code, ANSYS. According to the verification results, it is expected that the suggested method will be useful to predict the forced response on the L$\acute{e}$vy plate with the distributed area or line loading conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6A
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• pp.1099-1106
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• 2001

본 논문에서는 IEEE 802.11a 표준안으로 확정된 OFDM(Orthogonal Frequency Division Multiplexing) 방식을 적용한 고속 무선 LAN의 최적 시스템을 설계하기 위하여 실내 채널 특성들을 분석하였다. 통계적 채널 모델링 및 JTC(Joint Technical Committee) 모델에서의 실내 및 실외 환경을 선택하여 채널에 따른 고속 무선 LAN 시스템을 모의 실험하였다. 또한 채널에 의한 열화를 보상하기 위하여 무선 LAN 표준안에 따른 긴 훈련 신호를 이용한 채널 등화기법인 LS(Least Square) 방식과 LMMSE(Linear Minimum Mean Square Error) 방식을 비교 분석하였다. LS 기법과 본 논문에서 제시한 LS 방식으로 채널의 지연 확산 rms(root mean square) 값을 추정한 후 LMMSE 기법을 사용한 경우의 차이점을 고찰하였다. 이러한 LMMSE 기법을 채택할 경우 LS 기법에 비해 실외환경과 같은 열악한 채널환경 하에서도 시스템 성능에 상당한 개선효과가 나타남을 확인할 수 있었다.