• The Transactions of the Korea Information Processing Society
• /
• v.5 no.1
• /
• pp.97-102
• /
• 1998

In the most cases of eigen value problems in the social sciences, the object matrix to analyze is real-valued symmetric matrix. And many cases of eigen value problems in this field needs 2-4 eigen pairs according to the magnitude of their absolute values. The methods to obtain eigen pairs by numerical computation using computer, we would face the problem of round off error because matrix computation needs a number of calculations. In this paper, an algorithm which make us to get some needed eigcn pairs according to the magnitude of their absolute values is designed. And in this algorithm, the power method is used to obtain some eigen pairs. This algorithm is expected to be effective by the reduction of the number of calculations.

• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.2
• /
• pp.106-112
• /
• 2007

This paper proposes a hybrid architecture algorithm for fast computation of DCT and DFT via recursive factorization. Recursive factorization of DCT-II and DFT transform matrix leads to a similar architectural structure so that common architectural base may be used by simply adding a switching device. Linking between two transforms was derived based on matrix recursion formula. Hybrid acrchitectural design for DCT and DFT matrix decomposition were derived using the generation matrix and the trigonometric identities and relations. Data flow diagram for high-speed architecture of Cooley-Tukey type was drawn to accommodate DCT/DFT hybrid architecture. From this data flow diagram computational complexity is comparable to that of the fast DCT algorithms for moderate size of N. Further investigation is needed for multi-mode operation use of FFT architecture in other orthogonal transform computation.

• Journal of Information Technology Services
• /
• v.3 no.2
• /
• pp.99-104
• /
• 2004

Conventional and public-key cryptography has been widely accepted as a base technology for the design of computer security systems. D-classes have the potential for application to conventional and public-key cryptography. However, there are very few results on D-classes because the computational complexity of D-class computation is NP-complete. This paper discusses the design of algorithms for the efficient computation of D-classes and the Java implementation of them. In addition, the paper implements the same D-class computation algorithms in C and shows the performance of C and Java programming languages for the computation-intensive applications by comparing their execution results.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.3
• /
• pp.91-102
• /
• 1994

For the analysis of textured image, it requires large storage space and computation time to calculate the matrix features such as SGLDM(Spatial Gray Level Dependence Matrix). NGLDM(Neighboring Gray Level Dependence Matrix). NSGLDM(Neighboring Spatial Gray Level Dependence Matrix) and GLRLM(Gray Level Run Length Matrix). In spite of a large amount of information that each matrix contains, a set of several correlated scalar features calculated from the matrix is not sufficient to approximate it. In this paper, we propose a new classifier for textured images based on these matrices in which the projected vectors of each matrix on the meaningful directions are used as features. In the proposed method, an unknown image is classified to the class of a known image that gives the maximum similarity between the projected model vector from the known image and the vector from the unknown image. In the experiment to classify images of agricultural products, the proposed method shows good performance as much as 85-95% of correct classification ratio.

• Journal of Institute of Convergence Technology
• /
• v.9 no.1
• /
• pp.1-6
• /
• 2019

Matrix multiplication is a fundamental mathematical operation that has numerous applications across most scientific fields. In this paper, we presents a parallel GPU computation algorithm for dense matrix-matrix multiplication using OpenGL compute shader, which can play a very important role as a fundamental building block for many high-performance computing applications. Experimental results on NVIDIA Quad 4000 show that the proposed algorithm runs about 208 times faster than previous CPU algorithm and achieves performance of 75 GFLOPS in single precision for dense matrices with matrix size 4,096. Such performance proves that our algorithm is practical for real applications.

• The Journal of the Acoustical Society of Korea
• /
• v.16 no.3E
• /
• pp.32-36
• /
• 1997

This study models mobile communication channels as a discrete finite Markovian process, and Markovian jump linear system having parallel Kalman filter type is applied. What is newly proposed in this paper is an equation for obtaining the transition matrix according to sampling time by using a weighted Gaussian sum approximation and its simple calculation process. Experiments show that the proposed method has superior performance and reuires computation compared to the existing MJLS using the ransition matrix given by a statistical method or from priori information.

• Journal of Communications and Networks
• /
• v.13 no.3
• /
• pp.211-213
• /
• 2011

In this paper, we propose a key agreement protocol using Sylvester Hadamard matrices. Users obtain their common key by using a matrix shared in advance. Matrix construction is very simple, and the computation is quite fast. The proposal will be useful for communication between two users, especially for those having low computing power.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.8
• /
• pp.1434-1439
• /
• 2008

Numerical methods for solving the state feedback control problem of linear time invariant system are presented in this paper. The methods are based on Haar wavelet approximation. The properties of Haar wavelet are first presented. The operational matrix of integration and its inverse matrix are then utilized to reduce the state feedback control problem to the solution of algebraic matrix equations. The proposed methods reduce the computation time remarkably. Finally a numerical example is illustrated to demonstrate the validity and applicability of the proposed methods.

• Journal of the Korean Physical Society
• /
• v.73 no.12
• /
• pp.1808-1813
• /
• 2018

I develop a transfer matrix algorithm for computing the geometric quantities of a square lattice polymer with nearest-neighbor interactions. The radius of gyration, the end-to-end distance, and the monomer-to-end distance were computed as functions of the temperature. The computation time scales as ${\lesssim}1.8^N$ with a chain length N, in contrast to the explicit enumeration where the scaling is ${\sim}2.7^N$. Various techniques for reducing memory requirements are implemented.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.7
• /
• pp.577-582
• /
• 2013

In this paper Legendre wavelets are used to approximate the solutions of linear time-invariant system. The Legendre wavelet and its integral operational matrix are presented and an efficient algorithm to solve the Sylvester matrix equation is proposed. The algorithm is based on the decomposition of the Sylvester matrix equation and the preorder traversal algorithm. Using the special structure of the Legendre wavelet's integral operational matrix, the full order Sylvester matrix equation can be solved in terms of the solutions of pure algebraic matrix equations, which reduce the computation time remarkably. Finally a numerical example is illustrated to demonstrate the validity of the proposed algorithm.