Asynchronous Controllability of Non-Homogeneous Markov Switch Generalized Asynchronous Boolean Control Networks With Deterministic Dwell Time

This study investigates the asynchronous controllability of non-homogeneous Markov switch generalized asynchronous Boolean control networks (NMHGABCNs) and random switching signals in these networks, aiming to follow a non-homogeneous Markov process. The controllability of the proposed networks is achieved using the discrepancy between the Markov chain mode and the control mode. Assisted by the semi-tensor product (STP), the algebraic forms of the NMHGABCNs are obtained, and the sufficient and necessary criteria for their asynchronous controllability are derived. The effectiveness of controllability is demonstrated through two examples, which validate the theoretical results.

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Publication Details

Journal
IEEE Transactions on Computational Biology and Bioinformatics
Published
2025-12-22
DOI
https://doi.org/10.1109/tcbbio.2025.3646694
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
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article

Asynchronous Controllability of Non-Homogeneous Markov Switch Generalized Asynchronous Boolean Control Networks With Deterministic Dwell Time

Fan Yang, Shihua Fu, Jie Zhong, Xianghui Su et al.
IEEE Transactions on Computational Biology and Bioinformatics
Gene Regulatory Network Analysis
article

Asynchronous Controllability of Non-Homogeneous Markov Switch Generalized Asynchronous Boolean Control Networks With Deterministic Dwell Time

Fan Yang, Shihua Fu, Jie Zhong, Xianghui Su, Hao Zhang
article en

Abstract

This study investigates the asynchronous controllability of non-homogeneous Markov switch generalized asynchronous Boolean control networks (NMHGABCNs) and random switching signals in these networks, aiming to follow a non-homogeneous Markov process. The controllability of the proposed networks is achieved using the discrepancy between the Markov chain mode and the control mode. Assisted by the semi-tensor product (STP), the algebraic forms of the NMHGABCNs are obtained, and the sufficient and necessary criteria for their asynchronous controllability are derived. The effectiveness of controllability is demonstrated through two examples, which validate the theoretical results.

IEEE Transactions on Computational Biology and BioinformaticsVol. 23(1)
Zhejiang Normal University (CN), Liaocheng University (CN), Taiyuan University of Technology (CN)
Openalex Percentile: Top 37%
Gene Regulatory Network Analysis
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