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Improved Stability and Stabilization Results for Stochastic Synchronization of Continuous-Time Semi-Markovian Jump Neural Networks With Time-Varying Delay.
- Source :
-
IEEE Transactions on Neural Networks & Learning Systems . Jun2018, Vol. 29 Issue 6, p2488-2501. 14p. - Publication Year :
- 2018
-
Abstract
- Continuous-time semi-Markovian jump neural networks (semi-MJNNs) are those MJNNs whose transition rates are not constant but depend on the random sojourn time. Addressing stochastic synchronization of semi-MJNNs with time-varying delay, an improved stochastic stability criterion is derived in this paper to guarantee stochastic synchronization of the response systems with the drive systems. This is achieved through constructing a semi-Markovian Lyapunov–Krasovskii functional together as well as making use of a novel integral inequality and the characteristics of cumulative distribution functions. Then, with a linearization procedure, controller synthesis is carried out for stochastic synchronization of the drive-response systems. The desired state-feedback controller gains can be determined by solving a linear matrix inequality-based optimization problem. Simulation studies are carried out to demonstrate the effectiveness and less conservatism of the presented approach. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ARTIFICIAL neural networks
*MACHINE learning
*CONTROL theory (Engineering)
Subjects
Details
- Language :
- English
- ISSN :
- 2162237X
- Volume :
- 29
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Neural Networks & Learning Systems
- Publication Type :
- Periodical
- Accession number :
- 129655409
- Full Text :
- https://doi.org/10.1109/TNNLS.2017.2696582