Robust stability condition for neutral-type neural networks with discrete and distributed delays
The robust exponential stability is investigated for a class of uncertain neutral-type neural networks with
discrete and distributed time-varying delays. By introducing a new vector Lyapunov-Krasovskii functional, using Jensen integral inequality,
free-weighting matrix method and linear matrix inequality(LMI)
techniques, delay-dependent sufficient conditions are obtained for
exponential stability of considered neural networks, which
generalize some previous results in the literature. Four examples
are given to show the less conservativeness of the obtained results.
Keywords: Global robust exponential stability; linear matrix inequality(LMI); uncertain neutral-type neural
Download Full-Text
ABOUT THE AUTHORS
Li-Yuan Wang
Dalian Jiaotong University
Xiu-Mei Li
Dalian Jiaotong University
Li-Yuan Wang
Dalian Jiaotong University
Xiu-Mei Li
Dalian Jiaotong University