Design of delay-range-dependent state estimators for discrete-time recurrent neural networks with interval time-varying delay

2008 ◽  
Author(s):  
Chien-Yu Lu ◽  
Jui-Chuan Cheng ◽  
Te-Jen Su
Keyword(s):  
Neural Networks ◽  
Discrete Time ◽  
Recurrent Neural Networks ◽  
Time Varying ◽  
Interval Time ◽  
Time Varying Delay ◽  
State Estimators ◽  
Varying Delay ◽  
Dependent State

scholarly journals Delay-Range-Dependent Global Robust Passivity Analysis of Discrete-Time Uncertain Recurrent Neural Networks with Interval Time-Varying Delay

2009 ◽  
Vol 2009 ◽  
pp. 1-14 ◽  
Author(s):  
Chien-Yu Lu ◽  
Chin-Wen Liao ◽  
Hsun-Heng Tsai
Keyword(s):  
Neural Networks ◽  
Discrete Time ◽  
Recurrent Neural Networks ◽  
Linear Matrix ◽  
Time Varying ◽  
Parameter Uncertainties ◽  
Interval Time ◽  
Time Varying Delay ◽  
Passivity Analysis ◽  
Varying Delay

This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with norm-bounded time-varying parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate type of Lyapunov functional, sufficient passivity conditions for the DRNNs are derived in terms of a family of linear matrix inequalities (LMIs). Two numerical examples are given to illustrate the effectiveness and applicability.

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