线性时间下可伸缩单长周期、单吸引子元胞自动机的合成

IF 0.7 4区 数学 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
B. Chakraborty, M. Dalui, B. Sikdar
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引用次数: 0

摘要

提出了任意长度的单长度周期、单吸引子元胞自动机的合成方法。在线性时间O(n)内合成的n细胞单长周期单吸引子元胞自动机(SACA)产生一个图案,并最终沉降到一个称为单长周期吸引子状态的点状态。围绕基于图的工具(称为下一个状态转换图)开发了一个分析框架,以探索三邻域一维元胞自动机的SACA规则的属性。这使得可以在恒定时间内从n细胞SACA的可用配置合成(n+1)细胞SACA,并在恒定时间内从n细胞SACA和m细胞SACA的可用配置合成(n+m)细胞SACA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis of Scalable Single Length Cycle, Single Attractor Cellular Automata in Linear Time
This paper proposes the synthesis of single length cycle, single attractor cellular automata (SACAs) for arbitrary length. The n-cell single length cycle, single attractor cellular automaton (SACA), synthesized in linear time O(n), generates a pattern and finally settles to a point state called the single length cycle attractor state. An analytical framework is developed around the graph-based tool referred to as the next state transition diagram to explore the properties of SACA rules for three-neighborhood, one-dimensional cellular automata. This enables synthesis of an (n+1)-cell SACA from the available configuration of an n-cell SACA in constant time and an (n+m)-cell SACA from the available configuration of n-cell and m-cell SACAs also in constant time.
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来源期刊
Advances in Complex Systems
Advances in Complex Systems 综合性期刊-数学跨学科应用
CiteScore
1.40
自引率
0.00%
发文量
121
审稿时长
6-12 weeks
期刊介绍: Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.
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