• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06b
• /
• pp.508-513
• /
• 2010

본 논문에서는 정칙 이진 행렬을 이용하여 유전 알고리즘의 성능을 개선할 수 있는 메타 유전 알고리즘을 설계한다. 정칙 이진 행렬은 유전 알고리즘에서 사용되는 이진 인코딩에서의 기저 변환에 중요하게 쓰일 수 있다. 이 논문에서는 정칙 이진 행렬의 기저 변화를 위한 아이디어와 더불어 정칙 이진 행렬의 표현과 재조합 연산에 대한 아이디어를 제시했던 연구들을 소개하고, 메타 유전 알고리즘을 위한 변이와 초기 해집단 생성, 평가에 대한 방법론을 제시한다.

• The Korean Journal of Applied Statistics
• /
• v.20 no.2
• /
• pp.373-385
• /
• 2007

The solution of the normal equation arising in a general linear model by the least square methods is not unique in general. Conventionally, SAS IML and G-inverse matrices are considered for such problems. In this paper, we provide a systematic solution procedures for SAS IML.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2002.11b
• /
• pp.216-219
• /
• 2002

정보통신의 발달과 인터넷의 확산으로 인해 정보보안의 필요성이 중요한 문제로 대두되면서 여러 종류의 암호 알고리즘이 개발되어 활용되고 있다. Substitution Permutation Networks(SPN)등의 블록 암호 알고리즘에서는 확산선형변환 행렬을 사용하여 안전성을 높이고 있다. 확산선형변환 행렬이 Maximum Distance Separable(MDS) 코드를 생성하면 선형 공격과 차분 공격에 강한 특성을 보인다. 본 논문에서는 선형변환 행렬이 MDS 코드를 생성하는 가를 판단하는 새로운 알고리즘을 제안한다. 입력 코드는 GF(2/sub□/)상의 원소들로 구성되며, 원소를 변수로 해석하여, 변수를 소거시키면서 선형변환행렬이 MDS 코드를 생성하는 가를 판단한다. 본 논문에서 제안한 알고리즘은 종래의 모든 정방 부분행렬이 정칙인가를 판단하는 알고리즘과 비교하여 연산 수행 시간을 크게 줄였다.

• Proceedings of the Korea Contents Association Conference
• /
• 2012.05a
• /
• pp.267-268
• /
• 2012

본 논문에서는 효과적인 영상암호를 위하여 영상을 여러 단계별 블록화 한 뒤 암호화 과정을 수행한다. 이러한 암호화 과정의 효과적인 연산을 위하여 기본 행렬 변환을 이용한 대수적 연산과 비정칙적 복잡 함수의 무작위적 특이성을 이용한다.

• The Korean Journal of Applied Statistics
• /
• v.26 no.5
• /
• pp.747-758
• /
• 2013

The covariance matrix is important in multivariate statistical analysis and a sample covariance matrix is used as an estimator of the covariance matrix. High dimensional data has a larger dimension than the sample size; therefore, the sample covariance matrix may not be suitable since it is known to perform poorly and event not invertible. A number of covariance matrix estimators have been recently proposed with three different approaches of shrinkage, thresholding, and modified Cholesky decomposition. We compare the performance of these newly proposed estimators in various situations.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.4
• /
• pp.721-731
• /
• 2017

In this study, principal component analysis methods using Lasso penalty are introduced. There are two popular methods that apply Lasso penalty to principal component analysis. The first method is to find an optimal vector of linear combination as the regression coefficient vector of regressing for each principal component on the original data matrix with Lasso penalty (elastic net penalty in general). The second method is to find an optimal vector of linear combination by minimizing the residual matrix obtained from approximating the original matrix by the singular value decomposition with Lasso penalty. In this study, we have reviewed two methods of principal components using Lasso penalty in detail, and shown that these methods have an advantage especially in applying to data sets that have more variables than cases. Also, these methods are compared in an application to a real data set using R program. More specifically, these methods are applied to the crime data in Ahamad (1967), which has more variables than cases.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.7
• /
• pp.1462-1470
• /
• 2003

According to the necessity about information security as well as the advance of IT system and the spread of the Internet, a variety of cryptography algorithms are being developed and put to practical use. In addition the technique about cryptography attack also is advanced, and the algorithms which are strong against its attack are being studied. If the linear transformation matrix in the block cipher algorithm such as Substitution Permutation Networks(SPN) produces the Maximum Distance Separable(MDS) code, it has strong characteristics against the differential attack and linear attack. In this paper, we propose a new algorithm which cm estimate that the linear transformation matrix produces the MDS code. The elements of input code of linear transformation matrix over GF$({2_n})$ can be interpreted as variables. One of variables is transformed as an algebraic formula with the other variables, with applying the formula to the matrix the variables are eliminated one by one. If the number of variables is 1 and the all of coefficient of variable is non zero, then the linear transformation matrix produces the MDS code. The proposed algorithm reduces the calculation time greatly by diminishing the number of multiply and reciprocal operation compared with the conventional algorithm which is designed to know whether the every square submatrix is nonsingular.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.1
• /
• pp.9-13
• /
• 1996

슬라이딩 모드 제어기의 실현시 발생하는 고주파 chattering 현상을 제거하기 위하여 본 논문에서는 스위칭 표면 행렬의 Range-space 동특성을 이용한 연속 시간 스위칭 다이나믹을 제안한다. 전체 폐루프 시스템은 정칙 변환에 의해 빠른 부시스템과 느린 부시스템으로 분해되어, 결국 전체 폐루프 시스템의 고유치는 각각 스위칭 표면 행렬의 Range-space와 Null-space의 동특성을 지배하는 부시스템들의 고유치들로 구성됨을 보인다. 그리고, 정합된 불확실성이 존재하는 경우 제안된 스위칭 다이나믹을 가진 제어 시스템의 응답은 일정 시간이 경과된 후 스위칭 평면의 임의의 영역으로 균일하게 유계된다는 것을 증명한다. 또한, 제어 입력의 크기에 대한 제약성을 만족하면서도 전체 제어 시스템의 정상 상태 오차를 감소시키기 위하여 두개의 스위칭 다이나믹을 도입한 수정된 슬라이딩 모드제어기를 제안한다.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1648-1649
• /
• 2007

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM(Support Vector Machines) makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller be with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems

• Computational Structural Engineering
• /
• v.11 no.1
• /
• pp.205-216
• /
• 1998

A solution method is presented to solve the eigenvalue problem arising in the dynamic analysis of nonclassicary damped structural systems with multiple eigenvalues. The proposed method is obtained by applying the modified Newton-Raphson technique and the orthonormal condition of the eigenvectors to the linear eigenproblem through matrix augmentation of the quadratic eigenvalue problem. In the iteration methods such as the inverse iteration method and the subspace iteration method, singularity may be occurred during the factorizing process when the shift value is close to an eigenvalue of the system. However, even though the shift value is an eigenvalue of the system, the proposed method provides nonsingularity, and that is analytically proved. Since the modified Newton-Raphson technique is adopted to the proposed method, initial values are need. Because the Lanczos method effectively produces better initial values than other methods, the results of the Lanczos method are taken as the initial values of the proposed method. Two numerical examples are presented to demonstrate the effectiveness of the proposed method and the results are compared with those of the well-known subspace iteration method and the Lanczos method.