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|Title:||State estimation for discrete-time neural networks with time-varying delay|
|Citation:||International Journal of Systems Science, 2012; 43(4):647-655|
|Publisher:||Taylor & Francis Ltd|
|Zhengguang Wu, Peng Shi, Hongye Su and Jian Chu|
|Abstract:||This article deals with the problem of delay-dependent state estimation for discrete-time neural networks with time-varying delay. Our objective is to design a state estimator for the neuron states through available output measurements such that the error state system is guaranteed to be globally exponentially stable. Based on the linear matrix inequality approach, a delay-dependent condition is developed for the existence of the desired state estimator via a novel Lyapunov functional. The obtained condition has less conservativeness than the existing ones, which is demonstrated by a numerical example.|
|Keywords:||neural networks; time-varying delay; state estimation; exponential stability; linear matrix inequality (LMI)|
|Rights:||© 2012 Taylor & Francis|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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