• 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 $O(2^n)$.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.75-78
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• 2006

GF(2)위에서 최대길이를 갖는 n-셀 90/150 셀룰라 오토마타의 각 셀은 길이가 $2^n-1$인 수열을 생성한다. 이러한 셀룰라 오토마타의 임의의 셀에 대한 출력수열은 다른 셀에 대한 출력수열의 위치를 이동함으로써 얻을 수 있다. 본 논문에서는 주어진 셀룰라 오토마타의 상태전이행렬의 특성다항식에 의한 동차 선형점화식을 만족하는 충격반응수열을 이용하여 셀들의 위상이동차를 계산하는 알고리즘을 제안한다.

• 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.

• 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.

• Journal of Korea Game Society
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• v.16 no.6
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• pp.59-68
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• 2016

Many researchers have paid attention to contents generation within the area of game artificial intelligence these days with various reasons. Efforts on automatic contents generation without game level designers' help were continuously progressed in various game contents. This study suggests an automatic map generation without an isolated cave using cellular automation enhanced by binary space partitioning(BSP). In other words, BSP makes it possible to specify the number of desired area and cellular automation reduces the time to search a path. Based upon our preliminary simulation results, we show the usefulness of our automatic map generation by applying the contents generation using cell automation, which is enhanced by BSP to games.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.558-563
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• 2021

Quantum-Dot Cellular Automata is a next-generation nanocircular design technology that is drawing attention from many research organizations not only because it is possible to design efficient circuits by overcoming the physical size limitations of existing CMOS circuits, but also because of its energy-efficient features. In this paper, one of the existing digital circuits, T flip-flop circuit, is proposed using QCA. The previously proposed T flip-flops are designed based on the majority gate, so the circuits are complex and have long delays. Therefore, the design of the XOR gate-based T flip-flop using cell interaction reduces circuit complexity and minimizes latency. The proposed circuit is simulated using QCADesigner, and the performance is compared and analyzed with the existing proposed circuits.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.441-447
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• 1999

본 논문은 복잡 적응 시스템의 분석 및 모델링을 위해, 인공생명의 기본 패러다임인 셀룰라 오토마타를 선택하여, 무정형의 구조를 가지며 투명한 자료 전파 특성을 갖는 셀룰라 신경 회로망의 설계하고 개발하는데 중점을 두었다. 우선, 신경 회로망의 불규칙한 구조를 발생학적으로 다루어 무정형의 은닉층을 생성하고, 다윈의 진화론을 적용하여 구조적 진화 및 선택을 통해 최적화된 신경 회로망을 설계하였다. 주변 셀의 상태를 감지하여 자신의 상태를 수정해나가는 방식의 셀룰라 오토마타의 투명한 신호 전파 모델로 자료 및 오차의 역전파에 적용하도록 고안하였고, 라마르크의 용불용설을 활용한 오차의역전파 학습 알고리즘을 유도하였다. 이러한 복잡 적응계의 학습 과정을 유도하여 시뮬레이션에서 그 타당성을 입증하였다. 시뮬레이션에서는 신경 회로망의 XOR 문제와 다중 입력 다중 출력 함수에 대한 근사화 문제를 풀었다.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.521-527
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• 2020

Quantum-dot cellular automata (QCA) is a technology that attracts attention as a next-generation digital circuit design technology, and several digital circuits have been proposed in the QCA environment. Content-addressable memory (CAM) is a storage device that conducts a search based on information stored therein and provides fast speed in a special process such as network switching. Existing CAM cell circuits proposed in the QCA environment have a disadvantage in that a required area and energy dissipation are large. The CAM cell is composed of a memory unit that stores information and a match unit that determines whether or not the search is successful, and this study proposes an improved QCA CAM cell by designing the memory unit in a multi-layer structure. The proposed circuit uses simulation to verify the operation and compares and analyzes with the existing circuit.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.10
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• pp.895-903
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• 2017

Quantum Cellular Automata(QCA) is one of the proposed techniques as an alternative solution to the fundamental limitations of CMOS. QCA has recently been extensively studied along with experimental results, and is attracting attention as a nano-scale size and low power consumption. Although the XOR gates proposed in the previous paper can be designed using the minimum area and the number of cells, there is a disadvantage that the number of added cells is increased due to the stability and the accuracy of the result. In this paper, we propose a gate that supplement for the drawbacks of existing XOR gates. The XOR gate of this paper reduces the number of cells by arranging AND gate and OR gate with square structure and propose a half-adder by adding two cells that serve as simple inverters using the proposed XOR gate. Also This paper use QCADesginer for input and result accuracy. Therefore, the proposed half-adder is composed of fewer cells and total area compared to the conventional half-adder, which is effective when used in a large circuit or when a half - adder is needed in a small area.