• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.264-267
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• 2008

Many researchers have studied synthesis method of 90/150 group CA. However, there is a lack of researches for synthesis method of 90/150 nongroup CA. In this paper we report some interesting properties of 90/150 multiple-attractor CA in which all of the cycles are of unit length. 90/150 multiple-attractor CA is a class of nongroup CA. And we propose a construction of 90/150 single-attractor CA. Also we construct 90/150 multiple-attractor CA derived from 90/150 single-attractor CA.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.411-417
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• 2007

In this paper, the connection among the attractor, the attractor neighborhood and the domain of influence are investigated. A necessary and sufficient condition of the existence of the quasi-attractor is established. Some results of Conley in [2] are generalized.

• Bulletin of the Korean Mathematical Society
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• v.53 no.2
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• pp.581-588
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• 2016

Komuro [3] proved that geometric Lorentz attractor does not satisfy the shadowing property. In this paper we study the condition under which geometric Lorenz attractor has the orbital shadowing property that is weaker than the shadowing property.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.142-146
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• 1994

This paper proposes an fill-factor algorithm that determines embedding parameters which are needed in optimal attractor reconstruction. For reliability test, using this algorithm, we reconstructs the attractor of numerical chaotic data such as Duffing equation, Lorenz equation and Rossler equation whose embedding parameters are known. Also we reconstructs the attractor of experimental data and evaluates correlation dimension. Experimental data used in this paper are 38 ECG data of AHA(American Heart Association) ECG database. For numerical chaotic data, correlation dimension and Lyapunov exponent of reconstructed attractor are very close to those of attractor using original coordinate system.

• Journal of Welding and Joining
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• v.18 no.5
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• pp.77-83
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• 2000

This study proposes the analysis and evaluation method of time series ultrasonic signal using the attractor analysis. Features extracted from time series signal analyze quantitatively characteristics of weld defects. For this purpose, analysis objective in this study is fractal dimension and attractor quadrant feature. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics resulting from distance shifts such as parts of head and flange even though the types of defects are identified. These difference in characteristics of weld defects enables the evaluation of unique characteristics of defects in the weld zone. In quantitative fractal feature extraction, feature values of 3.848 in the case of part of head(crack) and 4.102 in the case of part of web(side hole) and 3.711 in the case of part of flange(crack) were proposed on the basis of fractal dimensions. Proposed attractor analysis and DAC in this study can enhance the precision rate of ultrasonic evaluation for defect signals of rail weld zone such as side hole and crack.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.20-26
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• 2003

This study proposes the construction of attractor quadrant method for high-precision cutting characteristics evaluation of non-ferrous metals. Also this paper aims to find the optimal cutting conditions of diamond turning machine by measuring surface form and roughness to perform the cutting experiment of non-ferrous metals, which are aluminum, with diamond tool. As well, according to change cutting conditions such as feed rate, using diamond turning machine to Perform cutting Processing, by measuring cutting force and surface roughness and according to cutting conditions the aluminum about cutting properties. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics and attractor quadrant characteristics. In quantitative quadrant feature extraction, 1,309 point in the case of A17075 (one quadrant) and 1,406 point (one quadrant) in the case of brass were proposed on the basis of attractor reconstruction. Proposed attractor quadrant method can be used for high-precision cutting characteristics evaluation of non-ferrous metals.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.5 no.1
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• pp.1-10
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• 2001

We investigate the relationship between the 0-tree and other trees in linear nongroup cellular automata. And we show that given a 0-basic path of 0-tree and a nonzero attractor ${\alpha}$ of a multiple attractor linear cellulara automata with two predecessor we construct an ${\alpha}$-tree of that multiple attractor linear cellular automata.

• Communications of the Korean Mathematical Society
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• v.20 no.4
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• pp.731-749
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• 2005

In this paper, we study the two dimensional g-Navier­Stokes equations on some unbounded domain ${\Omega}\;{\subset}\;R^2$. We prove the existence of the global attractor for the two dimensional g-Navier­Stokes equations under suitable conditions. Also, we estimate the dimension of the global attractor. For this purpose, we exploit the concept of asymptotic compactness used by Rosa for the usual Navier-Stokes equations.

• East Asian mathematical journal
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• v.32 no.3
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• pp.377-385
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• 2016

Global attractor is a basic concept to study the long-time behavior of solutions of the various equations. This paper is investigated with the existence of a global attractor for the beam equation $$u_{tt}+{\Delta}^2u-{\nabla}{\cdot}\{{\sigma}({\mid}{\nabla}u{\mid}^2){\nabla}u\}+f(u)+a(x)g(u_t)=h,$$ using multipliers technique and Nakao's Lemma.

• Journal of the Chungcheong Mathematical Society
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• v.15 no.1
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• pp.75-85
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• 2002

Let X be a compact metric space and let f be a continuous relation on X. Let U be an attractor block for f and let A bean attractor determined by U. Then there exists a continuous function ${\lambda}^{-1}:X{\rightarrow}[0,1]$ such that ${\lambda}^{-1}(0)=A$, ${\lambda}^{-1}(1)=X-B(A,U)$, and $M({\lambda},f)(x)$ < ${\lambda}(x)$ for all $x{\in}B(A,U)-A$.