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Reachable sets bounding for generalized neural networks with interval time-varying delay and bounded disturbances
journal contribution
posted on 2018-05-01, 00:00 authored by M V Thuan, Hieu Tran Manh, Hieu TrinhHieu TrinhThis paper deals with the problem of finding outer bound of forwards reachable sets and interbound of backwards reachable sets of generalized neural network systems with interval nondifferentiable time-varying delay and bounded disturbances. Based on constructing a suitable Lyapunov–Krasovskii functional and utilizing some improved Jensen integral-based inequalities, two sufficient conditions are derived for the existence of: (1) the smallest possible outer bound of forwards reachable sets and (2) the largest possible interbound of backwards reachable sets. These conditions are delay dependent and in the form of matrix inequalities, which therefore can be efficiently solved by using existing convex algorithms. Three numerical examples with simulation results are provided to demonstrate the effectiveness of our results.
History
Journal
Neural computing and applicationsVolume
29Issue
10Pagination
783 - 794Publisher
SpringerLocation
Berlin, GermanyPublisher DOI
ISSN
0941-0643eISSN
1433-3058Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2016, Natural Computing Applications ForumUsage metrics
Keywords
generalized neural networksforwards reachable setsbackwards reachable setsLyapunov-Krasovskii functionallinear matrix inequalitiesScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer ScienceGLOBAL EXPONENTIAL STABILITYASYMPTOTIC STABILITYLINEAR-SYSTEMSCLUSTER SYNCHRONIZATIONH-INFINITYDISCRETECRITERIADESIGNArtificial Intelligence and Image Processing
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