Title :
Improved Global Robust Stability Criteria for Delayed Neural Networks
Author :
Shen, Tao ; Zhang, Yong
Author_Institution :
Univ. of Jinan, Jinan
Abstract :
New criteria for the uniqueness and global robust stability of the equilibrium point of the interval Hopfield-type delayed neural networks are presented in the form of linear matrix inequality. An example is given to show the effectiveness of the obtained results.
Keywords :
Hopfield neural nets; linear matrix inequalities; stability criteria; global robust stability criteria; interval Hopfield-type delayed neural networks; linear matrix inequality; Delay effects; Differential equations; Hopfield neural networks; Linear matrix inequalities; Neural networks; Neurons; Robust stability; Robustness; Sufficient conditions; Symmetric matrices; Dynamical interval neural networks; equilibrium point; global robust stability;
Journal_Title :
Circuits and Systems II: Express Briefs, IEEE Transactions on
DOI :
10.1109/TCSII.2007.898467
