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- Title
Improved Delay-Dependent Stability Analysis for Neural Networks with Interval Time-Varying Delays.
- Authors
Tian, Jun-kang; Liu, Yan-min
- Abstract
The problem of delay-dependent asymptotic stability analysis for neural networks with interval time-varying delays is considered based on the delay-partitioning method. Some less conservative stability criteria are established in terms of linear matrix inequalities (LMIs) by constructing a new Lyapunov-Krasovskii functional (LKF) in each subinterval and combining with reciprocally convex approach. Moreover, our criteria depend on both the upper and lower bounds on time-varying delay and its derivative, which is different from some existing ones. Finally, a numerical example is given to show the improved stability region of the proposed results.
- Subjects
STABILITY theory; ARTIFICIAL neural networks; TIME-varying systems; LINEAR matrix inequalities; LYAPUNOV functions; MATHEMATICAL bounds
- Publication
Mathematical Problems in Engineering, 2015, Vol 2015, p1
- ISSN
1024-123X
- Publication type
Article
- DOI
10.1155/2015/705367