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Stability analysis of activation‐inhibition Boolean networks with stochastic function structures
Author(s) -
Zhao Guodong,
Liang Shuang,
Li Haitao
Publication year - 2020
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.6529
Subject(s) - boolean network , boolean function , product term , mathematics , equivalence (formal languages) , function (biology) , and inverter graph , parity function , two element boolean algebra , standard boolean model , set (abstract data type) , discrete mathematics , boolean expression , pure mathematics , algebra over a field , computer science , evolutionary biology , biology , programming language , filtered algebra
This paper analyzes the stability of activation‐inhibition Boolean networks with stochastic function structures. First, the activation‐inhibition Boolean networks with stochastic function structures are converted to the form of logical networks by the method of semitensor product of matrices. Second, based on the obtained algebraic forms, we use matrices to denote the index set of possible logical operators and transition probabilities for activation‐inhibition Boolean networks. Third, equivalence criterions are presented for the stabilities analysis of activation‐inhibition Boolean networks with stochastic function structures. Finally, an example is given to verify the validity of the results.