• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.301-305
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• 1996

$\mu$ theory can handle the parametric uncertainty and produces more non-conservative controller than H$_{\infty}$ control theory. However an existing solution of the theory, D-K iteration, creates a controller of huge order and cannot handle the real or mixed real-complex perturbation sets. In this paper, we use genetic algorithms to solve these problems of the D-K iteration method. The Youla parameterization is used to obtain all stabilizing controllers and the genetic algorithms determines the values of the state feedback gain, the observer gain, and Q parameter to minimize $\mu$, the structured singular value, of given system. From an example, we show that this method produces lower order controller which controls a real parameter-perturbed plant than D-K iteration method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5826-5841
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• 2019

In our previous research, we proposed a tag emotion-based item recommendation scheme. The ternary associations among users, items, and tags are described as a three-order tensor in order to capture the emotions in tags. The candidates for recommendation are created based on the latent semantics derived by a high-order singular value decomposition technique (HOSVD). However, the tensor is very sparse because the number of tagged items is smaller than the amount of all items. The previous research do not consider the previous behaviors of users and items. To mitigate the problems, in this paper, the item-based collaborative filtering scheme is used to build an extended data. We also apply the probabilistic ranking algorithm considering the user and item profiles to improve the recommendation performance. The proposed method is evaluated based on Movielens dataset, and the results show that our approach improves the performance compared to other methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1689-1698
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• 1998

In this paper, we present a new method for estimating the parameters of transient-type signal in additive white Gaussian noise. This method makes use of the truncated singular value decomposition of an extended-order auto-correlation-like matrix based on the linear-prediction model. The method is tested on data consisting of two exponentially dampled sinusoidal signals with the same damping factor and different damping factor. Simulation results are illustrated to demonstrate the better performance of the method applied to the auto-correlation-like matrix than that applied to the data matrix.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.77-82
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• 2010

An analytical method for robust design of the multi-loop proportional-integral (PI) controller is proposed for various types of multi-delay processes. On the basis of the direct synthesis and generalized IMC-PID approach, the analytical tuning rules of the multi-loop PI controller are firstly derived for achieving the desired closed-loop response, and the structured singular value synthesis is then utilized for the tradeoffs between the robust stability and performance by adjusting only one design parameter (i.e., the closed-loop time constant). To verify the superiority of the proposed method, the simulation studies have been conducted on a wide variety of multivariable processes. The multi-loop PI controller designed by the proposed method shows a fast, well-balanced and robust response with the minimum integral absolute error (IAE) in compared with other renowned methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.980-986
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• 2008

Spatial multiuser access is investigated for the reverse link of multiuser multiple-input multiple-output (MIMO) systems. In particular, we consider two alternative a aches to spatial multiuser access that adopt the same detection algorithm at the base station: one is a closed-loop approach based on singular value decomposition (SVD) of the channel matrix, whereas the other is an open-loop approach based in space-time block coding (STBC). We develop multiuser detection algorithms for these two spatial multiuser access schemes based on the minimum mean square error (MMSE) criterion. Then, we compare the bit error rate (BER) performance of the two schemes and a single-user MIMO scheme. Interestingly, it is found that the STBC approach can provide much better BER performance than the SVD approach as well as than a single-user MIMO scheme.

• KSBB Journal
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• v.16 no.4
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• pp.381-388
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• 2001

A program for integrated gene expression profile analysis such as hierarchical clustering, K-means, fuzzy c-means, self-organizing map(SOM), principal component analysis(PCA), and singular value decomposition(SVD) was made for DNA chip data anlysis by using Matlab. It also contained the normalization method of gene expression input data. The integrated data anlysis program could be effectively used in DNA chip data analysis and help researchers to get more comprehensive analysis view on gene expression data of their own.

• Bulletin of the Korean Chemical Society
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• v.24 no.7
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• pp.971-974
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• 2003

By utilizing singular value decomposition (SVD) and shift averaged Harr wavelet transform (WT) with a set of Daubechies wavelet coefficients (1/2, -1/2), a method that can simultaneously eliminate an unwanted large solvent peak and noise peaks from NMR data has been developed. Noise elimination was accomplished by shift-averaging the time domain NMR data after a large solvent peak was suppressed by SVD. The algorithms took advantage of the WT, giving excellent results for the noise elimination in the Gaussian type NMR spectral lines of NMR data pretreated with SVD, providing superb results in the adjustment of phase and magnitude of the spectrum. SVD and shift averaged Haar wavelet methods were quantitatively evaluated in terms of threshold values and signal to noise (S/N) ratio values.

• ETRI Journal
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• v.33 no.4
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• pp.652-655
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• 2011

In this letter, we propose a new compression method for a high dimensional support vector machine (SVM). We used singular value decomposition (SVD) to compress the norm part of a radial basis function SVM. By deleting the least significant vectors that are extracted from the decomposition, we can compress each vector with minimized energy loss. We select the compressed vector dimension according to the predefined threshold which can limit the energy loss to design criteria. We verified the proposed vector compressed SVM (VCSVM) for conventional datasets. Experimental results show that VCSVM can reduce computational complexity and memory by more than 40% without reduction in accuracy when classifying a 20,958 dimension dataset.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.125-127
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• 2000

협력적 여과는 사용자의 아이템에 대한 단계적 평가에 기초하여 그 평가 패턴이 유사한 사용자를 찾아 그 사용자들이 선호한 아이템을 상대방에게 교차 추천을 해주는 방법이다. 따라서, 유사한 사용자를 찾는 방법이 중요한 문제가 되며, 현재까지 여러 가지 방법들이 제안되어 왔다. 순수한 협력적 여과 방법은 n차원 공간에서 사용자를 모델링하여 가장 유사한 이웃을 찾는다. 이러한 모델링의 문제점은 사용자가 평가한 아이템의 집합은 전체 아이템의 집합에 비해서 극히 작으므로 유사한 사용자를 찾기 위해서는 충분한 수의 아이템에 대해서 평가해야 한다는 것이다. 따라서, 본 논문에서는 유사란 사용자를 찾기 위해서 충분한 수의 평가를 요구하는 명백하게 사용자의 평가를 비교하는 것 대신에 특징 가중치에 초하여 사용자를 비교하는 방법을 사용하고 사용하는 방법의 정확성을 높일 수 있는 임계값을 제안하고자 한다.

• ETRI Journal
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• v.43 no.1
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• pp.152-162
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• 2021

In the last few years, detection has become a powerful methodology for network protection and security. This paper presents a new detection scheme for data recorded over a computer network. This approach is applicable to the broad scientific field of information security, including intrusion detection and prevention. The proposed method employs bidimensional (time-frequency) data representations of the forms of the short-time Fourier transform, as well as the Wigner distribution. Moreover, the method applies matrix factorization using singular value decomposition and principal component analysis of the two-dimensional data representation matrices to detect intrusions. The current scheme was evaluated using numerous tests on network activities, which were recorded and presented in the KDD-NSL and UNSW-NB15 datasets. The efficiency and robustness of the technique have been experimentally proved.