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Stability and Stabilization in Probability of Probabilistic Boolean Networks.

Authors :
Huang, Chi
Lu, Jianquan
Zhai, Guisheng
Cao, Jinde
Lu, Guoping
Perc, Matjaz
Source :
IEEE Transactions on Neural Networks & Learning Systems; Jan2021, Vol. 32 Issue 1, p241-251, 11p
Publication Year :
2021

Abstract

This article studies the stability in probability of probabilistic Boolean networks and stabilization in the probability of probabilistic Boolean control networks. To simulate more realistic cellular systems, the probability of stability/stabilization is not required to be a strict one. In this situation, the target state is indefinite to have a probability of transferring to itself. Thus, it is a challenging extension of the traditional probability-one problem, in which the self-transfer probability of the target state must be one. Some necessary and sufficient conditions are proposed via the semitensor product of matrices. Illustrative examples are also given to show the effectiveness of the derived results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2162237X
Volume :
32
Issue :
1
Database :
Complementary Index
Journal :
IEEE Transactions on Neural Networks & Learning Systems
Publication Type :
Periodical
Accession number :
148040173
Full Text :
https://doi.org/10.1109/TNNLS.2020.2978345