• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.3
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• pp.3-8
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• 2010

There are some efficient brute force algorithm for factorization. Fermat's factorization is one of the way of brute force attack. Fermat's method works best when there is factor near the square-root. This paper shows that why Fermat's method is effective and verify that there are only one answer. Because there are only one answer, we can start Fermat's factorization anywhere. Also, we convert from factorization to finding square number.

• Journal of the Korean Mathematical Society
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• v.34 no.3
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• pp.533-541
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• 1997

Unique factorization of 2-dimensional complete intersection is investiagted by using the determinant method introduced by D. Eisenbud.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.290-297
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• 1999

In interior point methods for linear programming, we must solve a linear system with a symmetric positive definite matrix at every iteration, and Cholesky factorization is generally used to solve it. Therefore, if Cholesky factorization is not done successfully, many iterations are needed to find the optimal solution or we can not find it. We studied methods for improving the numerical stability of Cholesky factorization and the accuracy of the solution of the linear system.

• Bulletin of the Korean Mathematical Society
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• v.39 no.3
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• pp.495-509
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• 2002

We propose variants of the modified incomplete Cho1esky factorization preconditioner for a symmetric positive definite (SPD) matrix. Spectral properties of these preconditioners are discussed, and then numerical results of the preconditioned CG (PCG) method using these preconditioners are provided to see the effectiveness of the preconditioners.

• Bulletin of the Korean Mathematical Society
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• v.42 no.1
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• pp.203-211
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• 2005

If a meromorphic solution of second order homogeneous linear differential equation is factorizable, then the right factor of the factorization of the solution has order not more than the coefficient's. And some asympotic properties of solutions are studied.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.630-633
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• 2003

최근에 조명의 표현 성능을 향상시키기 위한 몇 가지 기술이 발전되었다. Homomorphic Factorization(HF) 기반의 새로운 기술은 BRDF에 근사화 하지는 않는다. 그러나 전체조명 장면에서의 isotropic BRDF의 full lighting computation을 대신할 수 있다. 이 방법으로 현재 그래픽 하드웨어의 일반적인 성능을 이용하여 최소 두개의 2D Texture로 Isotropic illumination 환경을 시뮬레이션 할 수 있었다.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.378-385
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• 2008

This paper aims to present a polynomial approach to the steady-state optimal filtering for delayed systems. The design of the steady-state filter involves solving one polynomial equation and one spectral factorization. The key problem in this paper is the derivation of spectral factorization for systems with delayed measurement, which is more difficult than the standard systems without delays. To get the spectral factorization, we apply the reorganized innovation approach. The calculation of spectral factorization comes down to two Riccati equations with the same dimension as the original systems.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.737-741
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• 2009

This paper addresses the factorization method to estimate the projective structure of a scene from feature (points) correspondences over images with occlusions. We propose both a column and a row space approaches to estimate the depth parameter using the subspace constraints. The projective depth parameters are estimated by maximizing projection onto the subspace based either on the Joint Projection matrix (JPM) or on the the Joint Structure matrix (JSM). We perform the maximization over significant observation and employ Tardif's Camera Basis Constraints (CBC) method for the matrix factorization, thus the missing data problem can be overcome. The depth estimation and the matrix factorization alternate until convergence is reached. Result of Experiments on both real and synthetic image sequences has confirmed the effectiveness of our proposed method.

• KIISE Transactions on Computing Practices
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• v.24 no.2
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• pp.93-98
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• 2018

Recommendation systems are used to provide items of interests for users to maximize a company's profit. Matrix factorization is frequently used by recommendation systems, based on an incomplete user-item rating matrix. However, as the number of items and users increase, it becomes difficult to make accurate recommendations due to the sparsity of data. To overcome this drawback, the use of text data related to items was recently suggested for matrix factorization algorithms. Furthermore, a word-level convolutional neural network was shown to be effective in the process of extracting the word-level features from the text data among these kinds of matrix factorization algorithms. However, it involves a large number of parameters to learn in the word-level convolutional neural network. Thus, we propose a matrix factorization algorithm which utilizes a character-level convolutional neural network with which to extract the character-level features from the text data. We also conducted a performance study with real-life datasets to show the effectiveness of the proposed matrix factorization algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.11
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• pp.54-64
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• 2010

Reed-Solomon (RS) codes are the most widely used error correcting codes in digital communications and data storage. Recently, Sudan found algorithm of list decoder for RS codes. List decoder has larger decoding radius than conventional hard-decision decoding algorithms and return more than one candidate polynomial. But, the algorithm includes interpolation and factorization step that demand massive computations. In this paper, an efficient architecture and processing schedule are proposed. The architecture consists of R-MAC, memories, and control unit. The R-MAC computes both of RC and PU steps that are main part of the factorization algorithm. The proposed architecture can achieve higher hardware utilization efficiency (HUE) and throughput by using efficient processing schedule and memory architecture. Also, the architecture can be designed flexibly with scalability for various applications. We design and synthesize our architecture using Dongbu-Anam $0.18{\mu}m$ standard cell library and the maximum clock frequency is 330MHz.