Title :
A Note on “Global Robust Stability Criteria for Interval Delayed Neural Networks Via an LMI Approach”
Author :
Shao, Jin-Liang ; Huang, Ting-Zhu
Author_Institution :
Sch. of Appl. Math., Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
A recently reported result concerning the global exponential robust stability of delayed neural networks is revisited. It is shown by a counter example that the result is invalid because the proof is incorrect, and then a modified version is given. The paper also presents an improved sufficient condition for global exponential robust stability of the neural networks with unbounded activation functions and time-varying delays. Finally, a numerical simulation is given to show the effectiveness of the obtained result.
Keywords :
asymptotic stability; delay systems; linear matrix inequalities; neurocontrollers; robust control; time-varying systems; LMI; delayed neural network; global exponential robust stability; time-varying delay; unbounded activation function; Counting circuits; Delay effects; Educational programs; Hydrogen; Linear matrix inequalities; Neural networks; Neurons; Robust stability; Robustness; Symmetric matrices; Dynamical interval neural networks; M-matrix; equilibrium analysis; global exponential robust stability;
Journal_Title :
Circuits and Systems II: Express Briefs, IEEE Transactions on
DOI :
10.1109/TCSII.2008.2008052
