• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.9A
• /
• pp.788-794
• /
• 2005

In this paper, we focus on the potential of dual polarized antennas in mobile system. thus, this paper designs exact dual polarized channel with Spatial Channel Model (SCM) and investigates the performance for certain environment. Using proposed the channel model; we know estimates of the channel capacity as a function of cross polarization discrimination (XPD) and spatial fading correlation. It is important that the MIMO channel matrix consists of Kronecker product dividable spatial and polarized channel. Through the channel characteristics, we propose an algorithm for the adaptation of transmit antenna configuration to time varying propagation environments. The optimal active transmit antenna subset is determined with equal power allocated to the active transmit antennas, assuming no feedback information on types of the selected antennas. We first consider a heuristic decision strategy in which the optimal active transmit antenna subset and its system capacity are determined such that the transmission data rate is maximized among all possible types. This paper then proposes singular values decision procedure consisting of Kronecker product with spatial and polarize channel. This method of singular value decision, which the first channel environments is determined using singular values of spatial channel part which is made of environment parameters and distance between antennas. level of correlation. Then we will select antenna which have various polarization type. After spatial channel structure is decided, we contact polarization types which have considerable cases It is note that the proposed algorithms and analysis of dual polarized channel using SCM (Spatial Channel Model) optimize channel capacity and reduce the number of transmit antenna selection compare to heuristic method which has considerable 100 cases.

• Journal of the Korean Mathematical Society
• /
• v.45 no.3
• /
• pp.631-644
• /
• 2008

In this paper, we present a new method for solving a nonlinear two-point boundary value problem with finitely many singularities. Its exact solution is represented in the form of series in the reproducing kernel space. In the mean time, the n-term approximation $u_n(x)$ to the exact solution u(x) is obtained and is proved to converge to the exact solution. Some numerical examples are studied to demonstrate the accuracy of the present method. Results obtained by the method are compared with the exact solution of each example and are found to be in good agreement with each other.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.101.1-101
• /
• 2001

This paper describes a grid mapping for a vision based mobile robot in uncertain indoor environment. The map building is a prerequisite for navigation of a mobile robot and the problem of feature correspondence across two images is well known to be of crucial Importance for vision-based mapping We use a stereo matching algorithm obtained by singular value decomposition of an appropriate correspondence strength matrix. This new correspondence strength means a correlation weight for some local measurements to quantify similarity between features. The visual range data from the reconstructed disparity image form an occupancy grid representation. The occupancy map is a grid-based map in which each cell has some value indicating the probability at that location ...

• Journal of the Korean Magnetic Resonance Society
• /
• v.4 no.2
• /
• pp.116-124
• /
• 2000

Singular value decomposition (SVD) has been used during past few decades in the advanced NMR data processing and in many applicable areas. A new modified SVD, piecewise polynomial truncated SVD (PPTSVD) was developed far the large solvent peak suppression and noise elimination in U signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L$_1$ problems. In TSVD, some unwanted large solvent peaks and noises are suppressed with a certain son threshold value while signal and noise in raw data are resolved and eliminated out in L$_1$ problem routine. The advantage of the current PPTSVD method compared to many SVD methods is to give the better S/N ratio in spectrum, and less time consuming job that can be applicable to multidimensional NMR data processing.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.26 no.6
• /
• pp.1461-1470
• /
• 2016

In side channel analysis, signal processing techniques can be used as preprocessing to enhance the efficiency and performance of analysis by reducing the noise or compressing the dimension. As signal processing techiniques using singular value decomposition can increase the information of main signal and reduce the noise by using the variance and tendency of signal, it is a great help to improve the performance of analysis. Typical techniques of that are PCA(Principal Component Analysis), LDA(Linear Discriminant Analysis) and SSA(Singular Spectrum Analysis). PCA and LDA can compress the dimension with increasing the information of main signal, and SSA reduces the noise by decomposing the signal into main siganl and noise. When applying each one or combination of these techniques, it is necessary to compare the performance. Therefore, it needs to suggest methodology of that. In this paper, we compare the performance of the three technique and propose using Sinal-to-Noise Ratio(SNR) as the methodology. Through the proposed methodology and various experiments, we confirm the performance and efficiency of each technique. This will provide useful information to many researchers in the field of side channel analysis.

• Journal of applied mathematics & informatics
• /
• v.5 no.1
• /
• pp.111-124
• /
• 1998

Existence results of multiple solutions are obtained un-der suitable conditions for impulsive integrodifferential boundary value problems on the half-line which may be singular at the boundary.

• Journal of the Korean Mathmatical Society
• /
• v.4 no.1
• /
• pp.1-4
• /
• 1967

• Kyungpook Mathematical Journal
• /
• v.31 no.1
• /
• pp.113-118
• /
• 1991

• 한국데이터정보과학회:학술대회논문집
• /
• 2003.05a
• /
• pp.133-133
• /
• 2003

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.11a
• /
• pp.267-271
• /
• 2007

본 논문은 원본이미지와 은닉이미지의 좋은 압축률과 만족할만한 이미지의 질, 그리고 외부공격에 강인한 이미지은닉의 한 방법으로 특이치 분해와 퍼지 군집화를 이용한 벡터양자화를 이용한 워터마킹 방법을 소개하였다. 실험에서는 은닉된 이미지의 비가시성과 외부공격에 대한 강인성을 증명하였다.