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• W3147365443 abstract "This paper is concerned with the state estima- tion problem for a class of memristor-based neural net- works with time-varying delay. A delay dependent condition is developed to estimate the neuron states through observed output measurements such that the error system is globally asymptotically stable. By constructing more effective Lyapunov functionals, and combining with Jensen integral inequality and free-weighting matrix approach, a less conservative sufficient condition for the existence of state estimator is formulated in terms of linear matrix inequality, which can be checked efficiently by using some standard numerical packages. Finally, a numerical example is given to demonstrate the effective- ness of the presented results." @default.
• W3147365443 created "2021-04-13" @default.
• W3147365443 creator A5044488451 @default.
• W3147365443 date "2015-01-01" @default.
• W3147365443 modified "2023-09-23" @default.
• W3147365443 title "State estimation for memristor-based neural networks with time-varying delays" @default.
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• W3147365443 hasPublicationYear "2015" @default.
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