Title :
Design of delay-range-dependent state estimators for discrete-time recurrent neural networks with interval time-varying delay
Author :
Lu, Chien-Yu ; Cheng, Jui-Chuan ; Su, Te-Jen
Author_Institution :
Dept. of Ind. Educ. & Technol., Nat. Changhua Univ. of Educ., Changhua
Abstract :
This paper performs a global stability analysis of a particular class of recurrent neural networks (RNN) with time-varying delay. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities (LMI) through the use of Leibniz-Newton formula and relaxation matrices. Finally, two numerical examples are given to illustrate the effectiveness of the given criterion.
Keywords :
delays; discrete time systems; linear matrix inequalities; neurocontrollers; robust control; state estimation; time-varying systems; Leibniz-Newton formula; Lipschitz continuous activation function; delay-dependent robust stability criteria; delay-range-dependent state estimator; discrete-time recurrent neural network; global stability analysis; linear matrix inequalities; relaxation matrices; time-varying delay; Delay effects; Delay estimation; Delay systems; Difference equations; Linear matrix inequalities; Neurons; Recurrent neural networks; Robust stability; Stability analysis; State estimation; Delay-range-dependent; interval time-varying delay; linear matrix inequality; state estimator;
Conference_Titel :
American Control Conference, 2008
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-2078-0
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2008.4587154
