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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 705367, 10 pages
Research Article

Improved Delay-Dependent Stability Analysis for Neural Networks with Interval Time-Varying Delays

School of Mathematics and Computer Science, Zunyi Normal College, Zunyi 563002, China

Received 20 October 2014; Accepted 27 November 2014

Academic Editor: P. Balasubramaniam

Copyright © 2015 Jun-kang Tian and Yan-min Liu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.