This paper establishes an exponential H∞ 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∞ 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. © 2009 IEEE.

New delay-dependent exponential H∞ synchronization for uncertain neural networks with mixed time delays

KARIMI, HAMID REZA;
2010-01-01

Abstract

This paper establishes an exponential H∞ 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∞ 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. © 2009 IEEE.
2010
H∞ performance; Linear matrix inequality (LMI); Neural networks (NNs); Synchronization; Time delay; Uncertainties; Control and Systems Engineering; Electrical and Electronic Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Human-Computer Interaction; Information Systems; Software
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1006090
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