6533b82afe1ef96bd128cbab
RESEARCH PRODUCT
Notice of Violation of IEEE Publication Principles: New Delay-Dependent Exponential $H_{\infty}$ Synchronization for Uncertain Neural Networks With Mixed Time Delays
Huijun GaoHamid Reza Karimisubject
Time delaysDiscretizationArtificial neural networkGeneral MedicineLinear matrixSynchronizationComputer Science ApplicationsExponential functionHuman-Computer InteractionDelay dependentControl and Systems EngineeringControl theoryElectrical and Electronic EngineeringSoftwareInformation SystemsMathematicsdescription
This paper establishes an exponential H infin synchronization method for a class of uncertain master and slave neural networks (MSNNs) with mixed time delays, where the mixed delays comprise different neutral, discrete, and distributed time delays. The polytopic and the norm-bounded uncertainties are separately taken into consideration. An appropriate discretized Lyapunov-Krasovskii functional and some free-weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H infin synchronization of the two coupled MSNNs regardless of their initial states. Detailed comparisons with existing results are made, and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2010-02-01 | IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) |