• Carbon letters
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• v.19
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• pp.57-65
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• 2016

Isroaniso matrix precursor synthesized from commercially available petroleum pitch was stabilized in air. The influence of oxygen mass gain during stabilization on the yield of matrix precursor was studied. Additionally, the influence of pressure on the yield of the stabilized matrix precursor in a real system was studied. The fourier transform infrared spectrometry (FTIR), thermogravimetric analysis (TGA), yield, yield rate, and yield impact were used to check the effect of stabilization and pressure on the yield of the matrix precursor and the end properties of the composite thereafter. The results showed that the yield increased with stabilization duration up to 20 h whereas it decreased for stabilization duration beyond 20 h. Further results showed that the stabilized matrix precursor for a duration of 5 h could withstand almost two-fold greater hot-pressing pressure without resulting in exudation as compared to that of a 1 h stabilized matrix precursor. The enhanced hot-pressing pressure significantly improved the yield of the matrix precursor. As a consequence, the densification and mechanical properties were increased significantly. Further, the matrix precursor stabilized for a duration of 20 h or more failed to provide proper and uniform binding of the reinforcement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.440-446
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• 2007

This paper addresses a new representation of DFT matrix via the Jacket transform based on the element inverse processing. We simply represent the inverse of the DFT matrix following on the factorization way of the Jacket transform, and the results show that the inverse of DFT matrix is only simply related to its sparse matrix and the permutations. The decomposed DFT matrix via Jacket matrix has a strong geometric structure that exhibits a block modulating property. This means that the DFT matrix decomposed via the Jacket matrix can be interpreted as a block modulating process.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.727-733
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• 2011

To understand the stock market structure it is very important to extract meaningful information by analyzing the correlation matrix between stock returns. Recently there has been many studies on the correlation matrix using the Random Matrix Theory. In this paper we adopt this random matrix methodology to a single-factor model and we obtain meaningful information on the correlation matrix. In particular we observe the analysis of the correlation matrix using the single-factor model explains the real market data and as a result we confirm the usefulness of the single-factor model.

• Honam Mathematical Journal
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• v.32 no.3
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• pp.399-412
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• 2010

In this paper, we consider a preconditioned accelerated overrelaxation (PAOR) method to solve systems of linear equations. We show the convergence of the PAOR method. We also give com-parison results when the coefficient matrix is an L- or H-matrix. Finally, we provide some numerical experiments to show efficiency of PAOR method.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.97-109
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• 2001

This article is devoted to “forgotten” and rarely used technique of matrix analysis, introduced in 60-70th and enhanced by authors. We will study the matrix trace operator and it’s differentiability. This idea generalizes the notion of scalar derivative for matrix computations. The list of the most common derivatives is given at the end of the article. Additionally we point out a close connection of this technique with a least square problem in it’s classical and generalized case.

• 전기의세계
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• v.22 no.4
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• pp.25-29
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• 1973

The computation of transmittances between arbitrary input and output nodes is of particular interest in the signal flow graph theory imput. The signal flow matrix [T] can be defined by [X]=-[T][X] where [X] and [Y] are input nose and output node matrices, respectively. In this paper, the followings are discussed; 1) Reduction of nodes by reforming the signal flow matrix., 2) Solution of input-output relationships by means of Gauss-Jordan reduction method, 3) Extension of the above method to the matrix signal flow graph.

• East Asian mathematical journal
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• v.29 no.3
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• pp.327-335
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• 2013

In this paper we consider the quadratic matrix equation which can be defined by $$Q(X)=AX^2+BX+C=0$$, where X is a $n{\times}n$ unknown complex matrix, and A, B and C are $n{\times}n$ given matrices with complex elements. We first introduce a couple of condition numbers of the equation Q(X) and present normwise condition numbers. Finally, we compare the results and some numerical experiments are given.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1639-1648
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• 1988

This paper deals with an analyzing method of the Korean syntax to implement a natural language understanding system. A matrix of the syntactic structure is derived by the structural features of the Korean language. The modificatoty and conceptual structures are extracted from the matrix and the predicate logic form is expressed by extracting the phrase, clause and conceptual structure in the analyzing process. This logic form constructs an knowledge base of the sentence and proposes the possibility of the inference.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.133-140
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• 2002

This paper investigates the applicability of the modified Lanczos method using the power technique, which was developed in the field of quantum physics, to the eigenproblem in the field of engineering mechanics by introducing matrix-powered Lanczos recursion and numerically evaluating the suitable power value. The matrix-powered Lanczos method has better convergence and less operation count than the conventional Lanczos method. By analyzing four numerical examples, the effectiveness of the matrix-powered Lanczos method is verified and the appropriate matrix power is also recommended.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.3
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• pp.51-56
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• 2012

The wing is a framework composed chiefly of skin, spars, ribs and can be simplified by matrix structure. In this paper, a displacement reliability of matrix structure is analysed by AFORM(Advanced First Order Reliability Method) and applicability is assessed.