• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.613-618
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• 2002

본 논문에서는 선형 TPMACA와 TPSACA의 특성을 이용하여 만들어진 트리구성알고리즘을 구성하고, TPSACA를 기반으로 하는 완전 해싱 알고리즘을 생성하고자 한다.

• Journal of the Chungcheong Mathematical Society
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• v.20 no.4
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• pp.577-585
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• 2007

We introduce the inverse shadowing property of geometric Lorenz flows and prove that the geometric Lorenz flows do not have the inverse shadowing property.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.114-117
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• 2002

본 논문에서는 미세한 차이를 식별할 수 있는 Chaos 이론을 숫자 패턴 인식 분야에 응용한다. 먼저, 숫자 영상의 특징 정보들을 시계열 데이터로 변환한 후, 제안된 수정된 에농 시스템으로부터 숫자 어트랙터를 재구성하고, 어트랙터의 특성 분석을 위해 프랙탈 차원 특징을 나타내는 정보 차원값을 이용하여 숫자를 인식하는 새로운 알고리즘을 제안함으로써, 특수한 용도로 숫자를 전문적으로 빠르고 정확하게 인식하는 고정도 숫자 인식 시스템을 구현하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.311-314
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• 1997

This paper presents recognition of high impedance fault patterns based of chaotic features using the Radial Basis Function Network(RBFN). The chaos attractor is reconstructed from the fault current data for pattern recognition. The RBFN successfully classifies the three kinds of fault pattems and one normal pattem.

• Journal of the Chungcheong Mathematical Society
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• v.29 no.1
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• pp.23-28
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• 2016

In this paper, we obtain close characterizations of flows near a saddle set which is one of the interesting unstable closed sets. Also, we consider some conditions that closed sets are to be stable.

• Journal of the Chungcheong Mathematical Society
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• v.32 no.4
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• pp.453-459
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• 2019

In this paper, we analyze the behaviour of flows near closed sets with compact boundary which contains no semi-orbits. Also, we give a condition that a closed invariant set is to be asymptotically stable.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.42-48
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• 1997

This paper has apparaised ability of speaker recognition and speech recognition using correlation dimension and Lyapunov dimension. In this method, speech was regarded the cahos that the random signal is appeared in determinisitic raising system. we deduced exact correlation dimension and Lyapunov dimension with searching important orbit from AR model power spectrum when reconstruct strange attractor using Taken's embedding theory. We considered a usefulness of speech recognition and speaker recognition using correlation dimension and Lyapunov dimension that characterized reconstruction attractor. As a result of consideration, which were of use more the speaker recognition than speech recognition, and in case of speaker recognition using Lyapunov dimension were much recognition rate more than speaker recognitions using correlation dimension.

• Korean Institute of Interior Design Journal
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• v.27 no.2
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• pp.175-185
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• 2018

The purpose of this study is to analyze the concept of 'Gradual Differentiation' in parametric design in terms of pure model logic and thus describe the distinctive feature from the previous design method. To meet the purpose, it explores external cases like gradual factor identified in natural phenomenon and artworks and define the inherent model principles into "Self-similarity', "Correlation', and 'Temporality' by examining these features in terms of algorithm. Meanwhile, it identified the principle of gradual model representation in parametric design within a single system called 'Attractor System' by applying these three concepts into specific methods of parametric design, and by interpreting the logical structure through the association among 'Attractor', 'Field', and 'Differentiation'. The creative utilization of parameter shows that gradual model process in parametric design does not mean a passive "conversion process" merely replacing natural parameter with algorithm; rather, it refers to an active "generating process" creating new meanings and value. By continuing this process of conceptual understanding and insight, creative perspective and practical ability to interpret parameter can be improved.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.226-235
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• 1998

This study proposes the analysis and evaluation of method of time series of ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. The features are extracted from time series data for analysis of weld defects quantitatively. For this purpose, analysis objectives in this study are fractal dimension, Lyapunov exponent, and strange attractor on hyperspace. The Lyapunov exponent is a measure of rate in which phase space diverges nearby trajectories. Chaotic trajectories have at least one positive Lyapunov exponent, and the fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal(correlation) dimensions and Lyapunov exponents show the mean value of 4.663, and 0.093 relatively in case of learning, while the mean value of 4.926, and 0.090 in case of testing in slag inclusion(weld defects) are shown. Therefore, the proposed chaotic feature extraction can be enhancement of precision rate for ultrasonic pattern recognition in defecting signals of weld zone, such as slag inclusion.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.89-96
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• 2003

This paper propose the new method witch is adopted in extracting character features and recognizing numeric characters using fractal dimension and modified Henon Attractor of the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from numeric character images And their feature hi converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of numeric character image after calculating Natural Measure and information bit which art meant fractal dimension. Finally, numeric character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An Experimental result shows 100% character classification rates for 10 digits and 90% of recognition rates in real situation and the recognition speed was 26 characters per second.