• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.319-344
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• 2020

Inverse analysis of non-linear reinforced concrete bridge pier using recursive Gaussian filtering for in-situ condition assessment is the main theme of this work. For this purpose, minimum variance unbiased estimation using unscented sigma points is adopted here. The uniqueness of this inverse analysis lies in its approach for strain based updating of engineering demand parameters, where appropriate bound and constrained conditions are introduced to ensure numerical stability and convergence. In this analysis, seismic input is also identified, which is an added advantage for the structures having no dedicated sensors for earthquake measurement. First, the proposed strategy is tested with a simulated example whose hysteretic properties are obtained from the slow-cyclic test of a frame to investigate its efficiency and accuracy. Finally, the experimental test data of a full-scale bridge pier is used to study its in-situ condition in terms of Park & Ang damage index. Overall the study shows the ability of the augmented minimum variance unbiased estimation based recursive time-marching algorithm for non-linear system identification with the aim to estimate the engineering damage parameters that are the fundamental information necessary for any future decision making for retrofitting/rehabilitation.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.91-98
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• 2011

In this paper, a multi-channel speech enhancement method using the linearly constrained minimum variance (LCMV) algorithm and a variable learning rate control is proposed. To control the learning rate for adaptive filters of the LCMV algorithm, the direction of arrival (DOA) is measured for each short-time input signal and the likelihood function of the target speech presence is estimated to control the filter learning rate. Using the likelihood measure, the learning rate is increased during the pure noise interval and decreased during the target speech interval. To optimize the parameter of the mapping function between the likelihood value and the corresponding learning rate, an exhaustive search is performed using the Bark's scale distortion (BSD) as the performance index. Experimental results show that the proposed algorithm outperforms the conventional LCMV with fixed learning rate in the BSD by around 1.5 dB.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.145-148
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• 2004

수중음향 시스템에서는 빔형성(Beamforming) 기법을 이용하여 목표물로부터 신호를 수신하고 이에 대한 정보를 얻어낼 수 있는데, 이러한 빔형성에 있어서 주엽(Mainlobe)의 빔폭(Beamwidth)과 부엽(Sidelobe)의 크기(Level)를 설계자가 목표하는 값에 최적화 시킬 수 있는 방법을 찾는 것이 무엇보다도 중요하다 최근 연구된 빔형성 기법의 대표적인 결과 중 하나로는 Phi1ip의 Weighting Function Method를 들 수 있다. 이러한 Phi1ip의 방법은 목표 주엽폭과 부엽 준위를 정하고 이를 적응필터 설계방식과 유사하게 적응시켜 나가는 과정을 이용한다. 그러나 이 방법은 주엽폭과 부엽 준위간의 상관관계로 인해서 원하는 부엽준위에 다다르지 못하거나 결과값을 얻는데 상당한 시간이 소요되는 경우가 자주 발생하는데, 이러한 단점을 보완하기 위하여 본 논문에서는 부엽 준위에 미치지 못하는 일부에 대하여 부분 최적화를 시켜 비교적 쉽게 설계를 만족시키는 새로운 알고리듬을 제안하고자 한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.330-336
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• 2016

In this paper, we studied for modified bartlett method to estimate desired information signal. Constrained length of bartlett method is assigned as one, and estimate desired information signal to compensate for delay time. Modified bartlett method is an optimum direction-of-arrival (DoA) estimation algorithm to apply delay time compensation to update optimum weight. The optimum weight is used linear constrained minimum variance method(LCMV). Through simulation, we are comparative analysis proposed algorithm and general Bartlett and MUSIC method. In desired signal estimation, condition simulation is an array antenna element numbers 6 or 9 and desired information signals number 3. We show the superior performance of the proposed algorithm relative to the existing method in estimation of desired information signal.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.291-297
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• 2016

In this paper, we are comparative analysis of exit algorithm and proposal algorithm for desired target direction of arrival estimation in correlation signal system. Proposed algorithm in this paper is to decrease target direction of arrival an estimation error probability using bayesian, maximum posterior, and MUSIC algorithm in order to decrease direction of arrival error probability as optimize and use linear constrained minimum variance to update weight value. Through simulation, we were comparative analysis proposed algorithm and exit MUSIC algorithm. In case SNR is 10dB and antenna element arrays are 9 and 12, We show the superior performance of the proposed method relative to the class method to decrease of signal estimation error probability about 11% and 13%, respectively.