New Exponential Stability Criteria for Neural Networks With Time-Varying Delay

This brief is concerned with the global exponential stability analysis problem for neural networks with time-varying delay. We construct an augmented Lyapunov-Krasovskii functional by using the decompositions of the time delays. In order to deal with the integral terms, the different integral intervals with the same interval length are unified. As a result, no extra inequalities are involved. The novel delay-dependent exponential stability criterion is proposed. Numerical examples are given to demonstrate the effectiveness of the obtained results.