• Journal of the Korean Statistical Society
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• v.13 no.2
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• pp.114-120
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• 1984

A parallel flats fraction for the $3^n$ design is defined as union of flats ${t}At=c_i(mod 3)}, i=1,2,\cdots, f$ and is symbolically written as At=C where A is rank r. The A matrix partitions the effects into n+1 alias sets where $u=(3^{n-r}-1)/2. For each alias set the f flats produce an ACPM from which a detection matrix is constructed. The set of all possible parallel flats fraction C can be partitioned into equivalence classes. In this paper, we develop some properties of a detection matrix and C.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.216-220
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• 1989

Direct calculation algorithm for the elements of A matrix is suggested for a single machine connected to the infinite bus. Excitation system and power system stabilizer are included. When A matrix is partitioned into seven submatrices, we can identify the location of non-zero elements and formula for each element. No matrix inversion and multiplication are necessary.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.125-133
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• 2002

Recently, Several inequalities Khatri-Rao Products of two four partitioned blocks positive definite real symmetry matrices are established by Liu in[Lin. Alg. Appl. 289(1999): 267-277]. We extend these results in two ways. First, the results are extended to two any partitioned blocks Hermitian matrices. Second, necessary and sufficient conditions under which these inequalities become equalities are presented.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.1027-1035
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• 2012

This paper proposes a new Levenberg-Marquardt algorithm that is accelerated by adjusting a Jacobian matrix and a quasi-Hessian matrix. The proposed method partitions the Jacobian matrix into block matrices and employs the inverse of a partitioned matrix to find the inverse of the quasi-Hessian matrix. Our method can avoid expensive operations and save memory in calculating the inverse of the quasi-Hessian matrix. It can shorten the training time for fast convergence. In our results tested in a large application, we were able to save about 20% of the training time than other algorithms.

• Journal of the Korean Statistical Society
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• v.10
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• pp.122-127
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• 1981

A parallel flats fraction for the $3^n$ factorial is symbolically written as $At=C=(C_1 C_2 \cdots C_f)$ where C is a rxf matrix and A is rxn matrix with rank r. It is shown that the set of all possible parallel flats fraction C for a given A and given size can be partitioned into equivalence classes. The number of those classes are enumerated in general.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.403-426
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• 1998

We present an algorithm to find an approximation for the stationary distribution for the general ergodic spatially-inhomogeneous block-partitioned upper Hessenberg form. Our approximation makes use of an associated upper block-Hessenberg matrix which is spa-tially homogeneous except for a finite number of blocks. We treat the MAP/G/1 retrial queue and the retrial queue with two types of customer as specific instances and give some numerical examples. The numerical results suggest that our method is superior to the ordinary finite-truncation method.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.211-215
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• 1989

The structure of A matrix of one machine connected to the infinite bus is described for a full model. The A matrix can be partitioned to submatrices which depend on the initial operating point and do not depend on it. When the dynamic properties for several different operating points are desired, those submatrices can be obtained through simple column operations. Furthermore, the elements of A matrix car be directly calculated from the manufacturer's data. RMS quantities of the state variables for the initial operating point are used. This approach can save the labor for calculating the elements of A matrix for the dynamic stability analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.44-57
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• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.39-49
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• 2015

Some characters and construction theorems of Pseudo Jacket Matrix which is generalized from Jacket Matrix introduced by Jacket Matrices: Construction and Its Application for Fast Cooperative Wireless signal Processing[27] was announced. In this paper, we proposed some examples of Pseudo inverse Jacket matrix, such as $2{\times}4$, $3{\times}6$ non-square matrix for the MIMO channel. Furthermore we derived MIMO singular value decomposition (SVD) pseudo inverse channel and developed application to utilize SVD based on channel estimation of partitioned antenna arrays. This can be also used in MIMO channel and eigen value decomposition (EVD).

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.58-69
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• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.