title: Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.
abstract: In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.
authors.affiliation: School of Economic Information and Engineering, Southwestern University of Finance and Economics, Chengdu, China.
authors.forename: Wenjun
authors.initials: W
authors.lastname: Xiong
authors.affiliation: Department of Mathematics, Southeast University, Nanjing, China.
authors.forename: Ragini
authors.initials: R
authors.lastname: Patel
authors.affiliation: Department of Mathematics, Southeast University, Nanjing, China.
authors.forename: Jinde
authors.initials: J
authors.lastname: Cao
authors.affiliation: School of Computing, Engineering and Mathematics, Western Sydney University, Sydney, NSW, Australia.
authors.forename: Wei Xing
authors.initials: WX
authors.lastname: Zheng
keywords: Biological neural networks; Economics; Learning systems; Neurons; Symmetric matrices; Synchronization