A new delay-independent condition for global robust stability of neural networks with time delays

2015 ◽  
Vol 66 ◽  
pp. 131-137 ◽  
Author(s):  
Ruya Samli
Keyword(s):  
Neural Networks ◽  
Robust Stability ◽  
Time Delays ◽  
Independent Condition ◽  
Global Robust Stability

Global robust stability of complex-valued recurrent neural networks with time-delays and uncertainties

2014 ◽  
Vol 07 (02) ◽  
pp. 1450016 ◽  
Author(s):  
Wei Zhang ◽  
Chuandong Li ◽  
Tingwen Huang
Keyword(s):  
Neural Networks ◽  
Robust Stability ◽  
Recurrent Neural Networks ◽  
Time Delays ◽  
Sufficient Conditions ◽  
Neural System ◽  
Multiple Time ◽  
Parameter Uncertainties ◽  
Global Robust Stability ◽  
Complex Valued

This paper focuses on the existence, uniqueness and global robust stability of equilibrium point for complex-valued recurrent neural networks with multiple time-delays and under parameter uncertainties with respect to two activation functions. Two sufficient conditions for robust stability of the considered neural networks are presented and established in two new time-independent relationships between the network parameters of the neural system. Finally, three illustrative examples are given to demonstrate the theoretical results.

A new criterion for global robust stability of interval neural networks with discrete time delays

2007 ◽  
Vol 31 (3) ◽  
pp. 561-570 ◽  
Author(s):  
Chuandong Li ◽  
Jinyu Chen ◽  
Tingwen Huang
Keyword(s):  
Neural Networks ◽  
Robust Stability ◽  
Discrete Time ◽  
Time Delays ◽  
Interval Neural Networks ◽  
Global Robust Stability ◽  
New Criterion

New global robust stability condition for uncertain neural networks with time delays

2014 ◽  
Vol 142 ◽  
pp. 267-274 ◽  
Author(s):  
Neyir Ozcan ◽  
Sabri Arik
Keyword(s):  
Neural Networks ◽  
Robust Stability ◽  
Stability Condition ◽  
Time Delays ◽  
Global Robust Stability ◽  
Uncertain Neural Networks
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