• International Journal of Reliability and Applications
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• 제4권3호
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• pp.97-111
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• 2003

By applying Theorem 2.6.4 (Fang and Zhang, 1990, p.66) the dispersion matrix of a multivariate power exponential (MPE) distribution is derived. It is shown that the MPE and the gamma distributions are related and thus the MPE and chi-square distributions are related. By extending Fang and Xu's Theorem (1987) from the normal distribution to the Univariate Power Exponential (UPE) distribution an explicit expression is derived for calculating the probability of an UPE random variable over an interval. A representation of the characteristic function (c.f.) for an UPE distribution is given. Based on the MPE distribution the probability density functions of the generalized non-central chi-square, the generalized non-central t, and the generalized non-central F distributions are derived.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권1호
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• pp.10-15
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• 2004

We present a state-space approach to make non-square linear systems strictly passive by using an input-dimensional parallel feedforward compensator. A necessary and sufficient condition for the existence of the parallel feedforward compensator is given by the static output feedback formulation, which enables to utilize linear matrix inequality. By modifying the structure of the compensator the additional technical assumption in the previous result [1] is removed. The effectiveness of the proposed method is illustrated by some numerical examples which can be stabilized by the proportional-derivative (PD) and proportional-derivative-integral (PID) control laws. The proposed control scheme can successfully replace the measurements of derivative terms in the control laws.

• Earthquakes and Structures
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• 제15권3호
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• pp.263-273
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• 2018

Operational modal analysis is being widely used in aerospace, mechanical and civil engineering. Common research fields include optimal design and rehabilitation under dynamic loads, structural health monitoring, modification and control of dynamic response and analytical model updating. In many practical cases, influence of noise contamination in the recorded data makes it difficult to identify the modal parameters accurately. In this paper, an improved frequency domain method called Enhanced Least Square Complex Frequency (eLSCF) is developed to extract modal parameters from noisy recorded data. The proposed method makes the use of pre-defined approximate mode shape vectors to refine the cross-power spectral density matrix and extract fundamental frequency for the mode of interest. The efficiency of the proposed method is illustrated using an example five story shear frame loaded by random excitation and different noise signals.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.683-687
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• 2007

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and Closed-Form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-Form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a Self-Tuning Weighted Least Square AOA algorithm that is a modified version of the conventional Closed-Form solution. In order to estimate the error covariance matrix as a weight, a two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

• 전자통신동향분석
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• 제13권4호통권52호
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• pp.59-69
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• 1998

The terminology of data prefetching is introduced, which includes stride, repeat distance, stall, pending stall, prefetch degree, prefetch distance, and prefetch offset. The effectiveness of hardware data prefetching in reducing cache misses is shown by presenting a square matrix multiplication example. Thereafter the pitfalls of prefetching and possible solutions are discussed.

• 대한수학회논문집
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• 제11권1호
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• pp.191-199
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• 1996

The strong shift equivalence of nonnegative integral square matrices is a necessary and sufficient condition for the topological conjugacy of topological Markov chains. In this paper we study the relation between strong shift equivalence and matrix conjugation.

• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2002년도 종합학술발표회 논문집 Vol.12 No.1
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• pp.380-383
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• 2002

본 논문에서는 20㎓~50㎓ 대역에서 2 차원 PBG(Photonic-Bandgap) 구조의 투과 특성을 RCWA(Rigorous coupled-wave analysis)방법에 의한 Transfer matrix로 해석하였다. Square lattice의 PBG 구조에 대하여 TE 편파에서 유전율의 변화와 결함(defect)의 유무에 대한 투과 특성을 고찰하였다.

• 대한토목학회논문집
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• 제8권4호
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• pp.33-39
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• 1988

본(本) 연구(硏究)는 matrix 해석(解析)(rigorous-method)을 이용(利用)하여 정밀(情密) traverse망(網)을 조정(調整)하는데 목적이 있다. 본(本) 연구(硏究) 결과(結果), matrix 해석(解析)에 의(依)한 엄밀해법(嚴密解法)으로도 복잡(複雜)한 traverse망(網)을 신속(迅速) 정확(正確)하게 처리(處理)할 수 있다. 또한 종래(從來)의 근사해법(approximate-method)을 본(本) matrix 해법(解法)의 조정(調整)값과 비교(比較)한 결과(結果) 평균(平均)제곱오차범위이내(誤差範圍以內)에 있고, 조정좌표(調整座標)값의 비교차(比較差)도 0.4~0.9mm정도(程度)로 나타났으며, 이로써 근사해법(approximate-method)의 실용적(實用的) 가치(價値)를 입증(立證)하게 되었다.

• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.129-134
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• 1995

The ordinary least square estimator of the disturbance variance in the pooled cross-sectional and time series regression model is shown to be asymptotically unbiased without any restrictions on the regressor matrix when the disturbances follow an equicorrelated error component models.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권2호
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• pp.125-130
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• 2016

The proposal of this study is a fast version of the conventional extreme learning machine (ELM), called pseudoinverse matrix decomposition based incremental ELM (PDI-ELM). One of the main problems in ELM is to determine the number of hidden nodes. In this study, the number of hidden nodes is automatically determined. The proposed model is an incremental version of ELM which adds neurons with the goal of minimization the error of the ELM network. To speed up the model the information of pseudoinverse from previous step is taken into account in the current iteration. To show the ability of the PDI-ELM, it is applied to few benchmark classification datasets in the University of California Irvine (UCI) repository. Compared to ELM learner and two other versions of incremental ELM, the proposed PDI-ELM is faster.