• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.267-273
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• 1998

셀룰라 오토마타 신경망은 저자에 의하여 개발된 신경망으로써 주변의 셀과 국소적인 연결을 가지며 셀룰라 오토마타의 발생규칙에 따라 생성되는 신경망이다. 셀룰라 오토마타 신경망을 간단히 줄여서 ECANS라고 한다. 본 신경망은 카오스 뉴런 모델을 사용하며 뉴런사이의 연결강도는 흥분성 또는 억제성 결합을 갖는다. 신호의 전달방식은 펄스의 형태로서 뉴런이 발화하면 '1' 발화하지 않으면 '0'이 된다. 본 논문에서는 셀룰라 오토마타를 구성하는 요소별 특징을 살펴보고 주어진 문제에 적합한 셀룰라 오토마타 신경망을 얻어내기 위한 진화방법으로서 DNA 코딩방법을 제안한다. 제안한 방법의 유효성을 시뮬레이션을 통하여 검증한다.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.83-86
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• 2006

본 논문에서는 합성된 90/150 그룹 셀룰라 오토마타의 특성다항식을 분석하고 이러한 셀룰라 오토마타의 구조와 특성다항식의 관계를 살펴본다. 또한 최대길이를 갖는 그룹 셀룰라 오토마타로부터 유도된 여원 셀룰라 오토마타의 구조가 선형 셀룰라 오토마타와 동형임을 밝힌다.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.593-598
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• 2015

Non-linear cellular automata is difficult to analyze mathematically than linear cellular automata. So it is difficult to identify reachable states and attractors of nongroup non-linear cellular automata than nongroup linear cellular automata. In this paper, we propose a new reachable table to overcome these problems. We can see the next state for all the states of the non-linear cellular automata by the proposed reachable table. In addition, we can identify reachable states and attractors by the reachable table.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.277-280
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• 2000

q가 소수의 거듭제곱의 형태일 때 GF(q)상에서의 1차원 셀룰라 오토마타의 여러 가지 특성들을 연구한다. 이러한 셀룰라 오토마타의 특성다항식에 관한 몇가지 특성들이 제시한다. Intermediate Boundary CA를 정의하고 Null Boundary CA와의 관계를 살펴본다.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.670-678
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• 2005

A Cellular Automaton(CA) is a dynamical system in which space and time are discrete, the state of each cell is unite and is updated by local interaction. Since the characteristics of CA is diffusion and local interaction, CA is used by crypto-systems and VLSI structure. In this study, we proposed a hash function based on the concept of 2-dimensional cellular automata and analyzed the proposed hash function.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.4
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• pp.3-10
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• 2005

Every cell position of a maximum-length 90/150 cellular automata(CA) generates the same pseudo-noise(PN) sequence corresponding to the characteristic polynomial of the CA with a phase shift. Unlike LFSRs, the phase shift is generally different between stages of a CA. In this paper, we propose an algorithm to compute relative phase shifts between stage of a CA. Our algorithm does not need Shank's algorithm to compute relative phase shifts and does not need any previous phase shifts to compute a phase shift. Moreover it is done in time $O(2^n)$.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.426-432
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• 2001

This paper is implementation of cellular automata neural network system using evolving hardware concept. This system is a living creatures'brain based on artificial life techniques. Cellular automata neural network system is based on the development and the evolution, in other words, it is modeled on the ontogeny and phylogney of natural living things. The phylogenetic mechanism are fundamentally non-deterministic, with the mutation and recombination rate providing a major source of diversity. Ontogeny is deterministic and local physics. Cellular automata is developed from initial cells, and evaluated in given environment. And genetic algorithms take a part in adaptation process. In this paper we implement this system using evolving hardware concept. Evolving hardware is reconfigurable hardware whose configuration si under the control of an evolutionary algorithm. We design genetic algorithm process for evolutionary algorithm and cells in cellular automata neural network for the construction of reconfigurable system. The effectiveness of the proposed system if verified by applying it to Exclusive-OR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1099-1104
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• 2009

Cellular Automata(CA) has been used as modeling and computing paradigm for a long time. While studying the models of systems, it is seen that as the complexity of the physical system increase, the CA based model becomes very complex and becomes to difficult to track analytically. Also such models fail to recognize the presence of inherent hierarchical nature of a physical system. In this paper we analyze the properties of GF($2^p$) multiplue attractor cellular automata(GF($2^p$) MACA) C and give a method of synthesis of C which is a special class of hierarchical cellular automata proposed as an alternative to solve the problem.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.493-499
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• 2008

Cellular Automata(CA) has been used as modeling and computing paradigm for a long time. And CA has been used to model many physical systems. While studying the models of such systems, it is seen that as the complexity of the physical system increase, the CA based model becomes very complex and becomes to difficult to track analytically. Also such models fail to recognize the presence of inherent hierarchical nature of a physical system. In this paper we give the characterization of Hierarchical Cellular Automata(HCA). Especially we analyze transition rules, characteristic polynomials and cyclic structures of HCA.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.521-523
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• 2003

본 논문에서는 프로그램 가능한 셀룰라 오토마타(Programmable Cellular Automata, PCA)를 이용한 곱셈기를 제안한다. 본 논문에서 제안한 구조는 연산 후 늘어나는 원소의 수를 제한하기 위하여 이용되는 기약다항식(irreducible polynomial)으로서 All One Polynomial(AOP)을 사용하며, 주기적 경계 셀룰라 오토마타(Periodic Boundary Cellular Automata, PBCA)의 구조적인 특성을 사용함으로써 정규성을 높이고 하드웨어 복잡도와 시간 복잡도를 줄일 수 있는 장점을 가지고 있다. 제안된 곱셈기는 시간적. 공간적인 면에서 아주 간단히 구성되어 지수연산을 위한 하드웨어 설계나 오류 수정 코드(error correcting code)의 연산에 효율적으로 이용될 수 있을 것이다.