• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.88-95
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• 1998

This paper is the result of constructing information processing system such as living creatures' brain based on artificial life techniques. The living things are best information processing system in themselves. One individual is developed from a generative cell. And a species of this individual has adapted itself to the environment through evolution. In this paper, we propose a new method of designing neural networks using biological inspired developmental and evolutionary concept. Ontogeny of organism is embodied in cellular automata(CA) and phylogeny of species is realized by evolutionary algorithms(EAs). We call 'Evolving Cellular Automata Neural Systems' as ECANSI. The connection among cells is determined by the rule of cellular automata. In order to obtain the best neural networks in given environment, we evolve the arragemetn of initial cells. The cell, that is a neuron of neural networks, is modeled on chaotic neuron with firing or rest state like biological neuron. A final output of network is measured by frequency of firing state. The effectiveness of the proposed scheme is verified by applying it to Exclusive-OR and parity problem.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.7-14
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• 1996

A particle system is defined as a collection of primitive particles that together represent irregular and ever-changing objects such as smoke, clouds, waterfalls, and explosions. A particle system can be a powerful tool for modeling a deformable object's motion and change of form since it has dynamic properties with time. As an object becomes more complicated and shows more chaotic behavior, however, we need much more parameters for describing its characteristics completely. Consequently, the conventional particle system leads to difficulty in managing all of the parameters properly since one parameter can affect the others. Moreover, motion equations for representing particles' behavior are usually approximated to gain speed-ups. The inevitable errors in calculating the equations can cause an unexpected outcome. In this paper, we present a new approach of applying fuzzy contol to mage particles' motion and attributes changes over time. We also give an implementation result of a fuzzy particle system to show the feasibility of the proposed method. Applications of the system to explosions, nebulae, volcanos, and grass are presented.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.271-280
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• 1999

인공신경망을 시계열예측에 적용하는 경우에 고려되어야 할 문제중, 특히 모형에 적합한 입력변수의 생성이 중요시되고 있는데, 이러한 분야는 인공신경망의 모형생성과정에서 입력변수에 대한 전처리기법으로써 다양하게 제시되어 왔다. 가장 최근의 입력변수 전처리기법으로써 제시되고 있는 신호처리기법은 전통적 주기분할처리방법인 푸리에변환기법(Fourier transforms)을 비롯하여 이를 확장시킨 개념인 웨이블릿변환기법(wavelet transforms) 등으로 대별될 수 있다. 이는 기본적으로 시계열이 다수의 주기(cycle)들로 구성된 상이한 시계열들의 집합이라는 가정에서 출발하고 있다. 전통적으로 이러한 시계열은 전기 또는 전자공학에서 주파수영역분할, 즉 고주파 및 저주파수를 분할하기 위한 기법에 적용되어 왔다. 그러나, 최근에는 이러한 연구가 다양한 분야에 활발하게 응용되기 시작하였으며, 그 중의 대표적인 예가 바로 경영분야의 재무시계열에 대한 분석이다 전통적으로 재무시계열은 장, 단기의사결정을 가진 시장참여자들간의 거래특성이 시계열에 각기 달리 가격으로 반영되기 때문에 이러한 상이한 집단들의 고유한 거래움직임으로 말미암아 예를 들어, 주식시장이 프랙탈구조를 가지고 있다고 보기도 한다. 이처럼 재무시계열은 다양한 사회현상의 집합체라고 볼 수 있으며, 그만큼 예측모형을 구축하는데 어려움이 따른다. 본 연구는 이러한 시계열의 주기적 특성에 기반을 둔 신호처리분석으로서 기존의 시계열로부터 노이즈를 줄여 주면서 보다 의미 있는 정보로 변환시켜 줄 수 있는 웨이블릿분석 방법론을 새로운 필터링기법으로 사용하여 현재 많은 연구가 진행되고 있는 인공신경망과의 모형결합을 통해 기존연구와는 다른 새로운 통합예측방법론을 제시하고자 한다. 본 연구에서 제시하는 통합방법론은 크게 2단계 과정을 거쳐 예측모형으로 완성이 된다. 즉, 1차 모형단계에서 원시 재무시계열은 먼저 웨이블릿분석을 통해서 노이즈가 필터링 되는 동시에, 과거 재무시계열의 프랙탈 구조, 즉 비선형적인 움직임을 보다 잘 반영시켜 주는 다차원 주기요소를 가지는 시계열로 분해, 생성되며, 이렇게 주기에 따라 장단기로 분할된 시계열들은 2차 모형단계에서 신경망의 새로운 입력변수로서 사용되어 최종적인 인공 신경망모델을 구축하는 데 반영된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1125-1130
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• 2014

The quantity and quality of contents containing information are sharply increasing with the rising network speed. In line with this rapid growth of information volume, a new communication protocol using the chaotic signal that can protect contents in communication is proposed as follows. The chaos system has the characteristic of unpredictability due to the sensitive initial values and the similarity of the signals with noise. We configured two chaos systems $F(X_n,Y_n)$ and $G(A_n,B_n)$ that have such characteristics and designed a data communication method using as encryption channel the same chaos signals generated by synchronizing the chaos system G with the F signals. The proposed method was verified with the encryption and decryption of images. The proposed method is different from the existing encrypted communication methods and is expected to lay the foundation for future studies in related areas.is an example of ABSTRACT format.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• Journal of KSNVE
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• v.7 no.1
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• pp.6-12
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• 1997

물리계에서 일어나는 동적 현상들은 선형해석 만으로 설명하기에는 불충분한 점이 많이 있다. 이는 기계구조물과 같은 실제 계의 진동이 기하학적 비선형성, 강성 의 비선형성 또는 경계조건의 비선형성 등의 영향으로 비선형적인 거동을 하기 때문 이다. 비선형 진동을 하는 기계 계는 우리 주변에서 쉽게 찾아 볼 수 있는데, 그 예로써 진자운동을 포함하여 동흡진기, 회전체계, 공작기계의 절삭운동, 건마찰 (dry friction) 관련 기계장치, 치차 및 기차의 바퀴와 레일 간의 접촉에서 볼수 있는 구분적 선형(piecewise linear) 진동계, 충격 진동계 등을 들 수 있다. 비선형 진동 연구는 limit cycle, 준주기운동(quasiperiodic motion), 점프현상(jump phenomena) 등의 인식에서 시작되어, 과거에는 설명이 안되어 회피되 왔던 랜덤(random) 형태의 비주기운동에 대한 연구로 까지 발전하고 있다. 비선형 진동을 다루는데 있어서 정규모드(normal mode)를 이용하는 방법이 있다. 일반적으로 선형계는 선형 정규모드 (linear normal mode)가 존재하는 것과 같이 비선형계에도 이와 유사한 정규모드가 존재한다는 사실이 연구 보고된 바 있다. 비선형계에 존재하는 정규모드는 계의 매개 변수(system parameters)에 따라 그 안정성이 바뀔 수 있으며, 만일 안정한 정규모드 가 어떤 매개변수에서 그 안정성이 바뀐다면 선형이론으로는 설명될 수 없는 새로운 운동이 일어나고 이러한 운동을 분기모드(bifurcation mode)라고 한다. 안정한 정규 모드 및 분기모드를 포함하여 비선형계를 다류는 것을 "정규모드 동역학(normal mode dynamics)"이라고 한다. 정규모드 동역학은 앞에서 언급된 비선형 현상들의 원인규명, 예측, 안정성해석 및 강제진동 해석을 가능하게 한다. 또한 최근에 활발히 연구되고 있는 혼돈운동(chaotic motion)의 해석도 가능하다. 이 글에서는 비선형 진동해석을 위한 정규모드 동역학에 대한 연구동향 및 기본 이론을 살펴 보았고, 그 적용 예를 통하여 실험결과와 비교 고찰 함으로써 정규모드 동역학의 적용성을 서술하여 보았다. 선형이론으로 이해하기 어려운 현상들에 대하여는 비선형의 관점에서 새롭게 접근하 려는 노력이 필요하며 비선형 이론에 대한 연구가 지속적으로 진행되어야 한다. 진행되어야 한다.

• Journal of The Korean Association of Information Education
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• v.14 no.2
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• pp.273-283
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• 2010

Emergent process or behaviour can be seen in many places, from any multicellular biological organism to traffic patterns, cities or organizational phenomena in computer simulations. Similarly, the concept of 'Green IT' refers to the way complex systems and patterns arise inevitably among groups due to environmental concerns in real world. Green IT has good possibility to evolve as very chaotic system, in which the number of interactions between components increases geometrically with the number of components, thus potentially allowing for many new types of behaviour to emerge. However, when Green IT system regards as a complexity one, there exits some attractors to derive and control the system. In this context, this paper presents a new model based on type-2 fuzzy logic system to identify and assess the attractors of Green IT system which correspond to Reach-Richness matrix of Green IT.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.103-123
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• 1999

Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets better than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U. S dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.6
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• pp.303-309
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• 2014

Chaos communication system can improve a system security due to characteristics of non-periodic, non-predictability, broadband signal and easy implementation. Also, chaos signal is sensitive to initial conditions of chaos map. By these reasons, security of chaos communication system is superior to digital communication system. BER performance of COOK modulation system is better than other chaos modulation systems, even if COOK modulation system uses an asynchronous receiver. However, security and safety of COOK modulated signal are worse than other chaos modulation systems, because information bits can be easily predicted from COOK modulated signal. In this paper, for security improvement of COOK modulated signal, we propose a novel Scrambling COOK modulation system by applying the scrambling method. Conventional COOK modulated signal can be predicted, because chaos signal is generated when data is only 1. However, proposed system cannot be predicted, because chaos signal is generated when data is 0 or 1. Therefore, security and safety of transmitted signal in scrambling COOK modulation system is superior to conventional COOK modulation system.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.231-236
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• 2009

Men's jewelry are thought to have a limited role as assisting women's jewelry or wedding gifts. The variety of designs are limited, and most of them are just copies of Japanese designs. In order to bring out a new kinds of variety in men's jewelry design, I have chosen architectural structures as a motif. Architectural structures have strong symbolical meanings that express man. They are powerful and challenging, and symbolize wealth and authority. Mario Botta, the wolrd famous architect is an architect with this kind of spirit. His architectural style does not lose his own color in a chaotic situation, but keeps the feeling of shape and space on the basis of locality. In this study I have started with a motif that may express specific and modem feelings by compressing the shape and spatial images of Mario Botta's structures minimally into men's jewelry in order to grope the possibilities in all aspects. I have done these in order to rediscover the beauty of the architectural structures by using the shape and spatial images that are found in Botta's structures, so that I may propose a new kind of men's jewelry with stresses on their shapes.