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

Abstract EN

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.