Title :
New delay-dependent robust stability condition for neutral-type neural networks with mixed time delays
Author_Institution :
Sch. of Sci., Dalian Jiaotong Univ., Dalian, China
Abstract :
The robust exponential stability is investigated for a class of uncertain neutral-type neural networks with both variable and distributed time-varying delays. By introducing a new vector Lyapunov-Krasovskii functional, using Jensen integral inequality and linear matrix inequality(LMI) techniques, two delay-dependent sufficient criteria are obtained for exponential stability of considered neural networks, which generalize some previous results in the literature. Three examples are given to show the less conservativeness of the obtained conditions.
Keywords :
Automation; Delay effects; Eigenvalues and eigenfunctions; Linear matrix inequalities; Mechatronics; Neural networks; Robust stability; Stability criteria; Symmetric matrices; Vectors; Global robust exponential stability; Jensen integral inequality; free-weighting matrix; linear matrix inequality(LMI); uncertain neutral-type neural networks;
Conference_Titel :
Industrial Mechatronics and Automation (ICIMA), 2010 2nd International Conference on
Conference_Location :
Wuhan, China
Print_ISBN :
978-1-4244-7653-4
DOI :
10.1109/ICINDMA.2010.5538183