Title :
A class of robust stability of neural networks with mixed delays
Author_Institution :
Dept. of Phys. & Inf. Eng., Jining Univ., Qufu, China
Abstract :
This paper considers a class of robust asymptotic stability of cellular neural network with mixed delays. By constructing a new Lyapunov-Krasovskii function, using the linear matrix inequality(LMI) method, a new robust asymptotic stability criterion of the neural networks with mixed delays is derived.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; control system analysis; delays; linear matrix inequalities; robust control; LMI; Lyapunov-Krasovskii function; cellular neural network; linear matrix inequality; mixed delays; robust asymptotic stability; Asymptotic stability; Circuit stability; Delay; Fractals; Neural networks; Robustness; Stability analysis; Linear matrix inequality (LMI); Mixed delays; Neural networks; Robust asymptotic stability;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
