Set stabilization of Boolean control networks based on bisimulations: A dimensionality reduction approach

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2025-02-07 DOI:10.1016/j.amc.2025.129338
Tiantian Mu , Jun-e Feng , Biao Wang
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Abstract

This paper exploits bisimulation relations, generated by extracting the concept of morphisms between algebraic structures, to analyze set stabilization of Boolean control networks with lower complexity. First, for two kinds of bisimulation relations, called as weak bisimulation and strong bisimulation relations, a novel verification method is provided by constructing the bisimulation matrices. Then the comparison for set stabilization of BCNs via two kinds of bisimulation methods is presented, which involves the dimensionality of quotient systems and dependency of the control laws on the original system. Moreover, the proposed method is also applied to the analysis of probabilistic Boolean control networks to establish the unified analysis framework of bisimulations. Finally, the validity of the obtained results is verified by the practical example.
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基于双仿真的布尔控制网络集镇定:一种降维方法
利用抽取代数结构间的态射概念生成的双仿真关系,分析了低复杂度布尔控制网络的集镇定问题。首先,针对弱双仿真和强双仿真两种双仿真关系,通过构造双仿真矩阵,提出了一种新的验证方法。然后比较了两种双仿真方法在商系统维数和控制律对原系统的依赖性方面对BCNs集镇定的影响。并将该方法应用于概率布尔控制网络的分析,建立了统一的双仿真分析框架。最后,通过实例验证了所得结果的有效性。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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