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A Delay-Range-Dependent Approach to Design State Estimator for Discrete-Time Recurrent Neural Networks With Interval Time-Varying Delay

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1 Author(s)
Chien-Yu Lu ; Dept. of Ind. Educ. & Technol., Nat. Changhua Univ. of Educ., Changhua

This paper deals with the problem of state estimation for discrete-time recurrent neural networks with interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. A delay-range-dependent condition for the existence of state estimators is proposed. Via available output measurements and solutions to certain linear matrix inequalities, general full-order state estimators are designed that ensure globally asymptotic stability. Two illustrative examples are given to demonstrate the effectiveness and applicability.

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Circuits and Systems II: Express Briefs, IEEE Transactions on  (Volume:55 ,  Issue: 11 )