• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 한국항해항만학회 2011년도 추계학술대회
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• pp.119-121
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• 2011

플로팅 구조물의 거동은 함체의 크기에 따라 많은 영향을 받는 것으로 알려져 있다. 그에 따라 함체의 거동을 표현하기 위한 해석모델은 해석의 단순성, 파랑하중과의 상호작용의 연계정도를 고려하여 그 형태 또한 달라지게 된다. 해석모델에는 함체에 발생하는 진동을 효과적으로 저감시키기 위한 진동저감시스템을 포함하는 경우도 있다. 함체의 해석모델에 진동저감시스템의 해석모델이 연계되면 이들 해석모형이 상호결함된 통합모형은 더욱 복잡한 경향을 가지게 된다. 본 연구에서는 함체의 해석모형을 강체거동을 하는 단순한 모형으로 가정하고 해석모형이 가지는 동적특성을 ICA기법을 통하여 효과적으로 추정하는 기법을 다룬다. 이를 위하여 실험과 ICA 기법을 이용하여 동적추정이 가능한지를 평가해보고 이를 플로팅 구조물에 적용하기 위한 기법을 다룬다.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (A)
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• pp.505-507
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• 2001

본 논문에서는 그람-슈미트 방법 및 독립 성분 해석(Independent Component Analysis, ICA)기법을 이용한 영상분리방법을 제안한다. 이 제안된 방법은 전처리 없이 ICA나 주성분 해석(Principal Component Analysis, PCA)을 이용한 것에 비해 개선된 영상을 보여준다. 이는 원래의 ICA 모델에 대하여 동일한 조건으로 일반화하여 그람-슈미트의 독립된 성분들이 ICA 모델에 충분히 동일하다는 것을 보여준다.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제31권12C호
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• pp.1257-1264
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• 2006

The carrier frequency offset causes loss of orthogonality between sub-carriers, thus leads to inter-carrier interference (ICI) in the OFDM symbol. This ICI causes severe degradation of the BER performance of the OFDM receiver. In this paper, we propose a new ICI cancellation algorithm which estimates frequency offset at the time-domain by using CP-ICA method to the received sub-carriers phase rotation. This algorithm is based on a statistical blind estimation method, which mainly utilizes the EVD, rotating phase and the $4^{th}-cumulants$. Since our scheme does not need any training and pilot symbol in estimation, we can expect enhanced bandwidth efficiency in OFDM systems. Simulation results show that the proposed frequency offset estimator is more accurate than the other estimators in $0.0<\varepsilon<1.0$.

• The KIPS Transactions:PartB
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• 제8B권4호
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• pp.389-394
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• 2001

본 논문에서는 독립 성분 해석(Independent Component Analysis, ICA) 기법과 인근 평균 및 정규화를 이용한 영상 분류 방법을 제안하였다. ICA에 잡음을 주어 영상을 분류하였을 때, 잡음에 대한 강인성을 증가시키기 위하여, 제안된 인근 평균 및 정규화를 전처리로 적용하였다. 제안된 방법은 전처리 없이 ICA에 주성분 해석(Principal Component Analysis, PCA)을 이용한 것에 비해 잡음에 대한 강인성을 증가시키는 것을 모의 실험을 통하여 확인하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.244-245
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• 2011

• Journal of KIISE:Information Networking
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• 제30권1호
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• pp.24-29
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• 2003

In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing schemes, which represents the information from observations as a set of random variables in the from of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other. which can be utilized in linear projection.. However, it has been known that ICA does not establish good performance in source separation by itself. Thus, in order to overcome this limitation, there have been many techniques that are designed to reinforce the good properties of ICA, which improves the mixed image separation. Unfortunately, the innovation process still needs to be studied since it yields inconsistent innovation process that is attached to the ICA, the expectation and maximization process is added. The results presented in this paper show that the proposed improves the image separation as presented in experiments.

• Journal of KIISE:Software and Applications
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• 제28권9호
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• pp.629-633
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• 2001

In this paper, we improve noise tolerance in image classification by combining ICA(Independent Component Analysis) with Normalization. When we add noise to the raw image data the degree of noise tolerance becomes N(0, 0.4) for PCA and N(0, 0.53) for ICA. However, when we use the preprocessing approach the degree of noise tolerance after Normalization becomes N(0, 0.75), which shows the improvement of noise tolerance in classification.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 한국항해항만학회 2011년도 춘계학술대회
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• pp.187-188
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• 2011

Independent component analysis (ICA) is a method separating the mixture of signals into statistically and mutually independent ones. It has been applied to not only the Cocktail-party problem but also EEG analysis using the EEG waveform, digital signal processing, image processing and cognitive technique field actively. This study aims to propose a procedure to estimate the modal responses and mode shapes of a floating structure by using the ICA method from measured responses of the floating structure.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제11권7호
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• pp.2328-2333
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• 2010

A direct boundary element method(DBEM) is widely applied for various acoustic wave problems. But this method has numerically non-unique solutions around the eigenfrequencies of the interior Dirichlet problem for the region enveloped with the acoustic boundary. A CHIEF method had been generally adopted to resolve the non-uniqueness problem and a new technique called ICA-Ring method has been suggested recently. In this paper, the characteristics of two techniques for avoiding the non-uniqueness of DBEM are examined and numerical codes embodying both techniques are developed. Numerical calculations are also carried out for an uniformly pulsating sphere, of which the results are investigated by including the comparisons with theoretical solutions.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(5)
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• pp.131-133
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• 2000

In this paper, we proposed a new method for localizing the independent sources generating the observed EEG based on independent component analysis (ICA). The performance of the algorithm was tested through computer simulations.