Improved Stability Criteria for Neural Networks with Additive Time-varying Delay Components

This paper investigated the problem of improved delay-dependent stability criteria for neural networks with two additive time-varying delay components. By constructing a more general type of Lyapunov functional and using effective mathematical technique to estimate the upper bound on the time derivative of the Lyapunov functional, some new delay-dependent stability criteria are derived in terms of linear matrix inequalities. The resulting stability criteria are of fewer matrix variables and less conservative than some existing ones. Numerical examples are given to illustrate the effectiveness and less conservativeness of the proposed method.