Stability and l1 Gain Analysis of Boolean Networks with Markovian Jump Parameters
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Article number | 7874087 |
Pages (from-to) | 4222-4228 |
Journal / Publication | IEEE Transactions on Automatic Control |
Volume | 62 |
Issue number | 8 |
Online published | 8 Mar 2017 |
Publication status | Published - Aug 2017 |
Link(s)
Abstract
This paper presents some results on stability and l1 gain analysis of Boolean networks with Markovian jump parameters. A necessary and sufficient condition for global stability of the concerned Boolean networks is given in terms of linear programming by utilizing the semi-tensor product of matrices and some properties of linear positive systems. Then the definition of Lyapunov function for stochastic Boolean networks is presented and a Lyapunov theorem is derived. Moreover, an l1 gain problem for stochastic Boolean networks with external disturbances is formulated and solved by a sufficient condition. Examples are shown to illustrate the effectiveness of the obtained results.
Research Area(s)
- Boolean networks (BNs), l1 gain, Markovian jump parameters, semi-tensor product (STP), stochastic Lyapunov function
Citation Format(s)
Stability and l1 Gain Analysis of Boolean Networks with Markovian Jump Parameters. / Meng, Min; Liu, Lu; Feng, Gang.
In: IEEE Transactions on Automatic Control, Vol. 62, No. 8, 7874087, 08.2017, p. 4222-4228.
In: IEEE Transactions on Automatic Control, Vol. 62, No. 8, 7874087, 08.2017, p. 4222-4228.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review