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Stability and synchronization for Riemann-Liouville fractional-order time-delayed inertial neural networks.
- Source :
-
Neurocomputing . May2019, Vol. 340, p270-280. 11p. - Publication Year :
- 2019
-
Abstract
- Abstract Stability and synchronization for Riemann-Liouville fractional-order time-delayed inertial neural networks are investigated in this paper. The model of fractional-order inertial neural network is proposed, which is more general and less conservative than the integer-order inertial neural network. Two lemmas on the composition properties of Riemann-Liouville fractional-order derivative and integral are given. Based on the composition properties of Riemann-Liouville fractional-order derivative, the original inertial system is transferred into conventional system through the proper variable substitution. Serval novel and effective feedback controllers are proposed for different cases of fractional-order time-delayed inertial neural networks, such that synchronization between the salve system and the master system can be achieved. In addition, stability conditions for a class of fractional-order time-delayed inertial neural networks are derived. Furthermore, three numerical examples are provided to show the validity and feasibility of the approaches. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ARTIFICIAL neural networks
Subjects
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 340
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 135376620
- Full Text :
- https://doi.org/10.1016/j.neucom.2019.03.005