Stability criteria with less variables for neural networks with time-varying delay

Abstract

In this paper, new delay-dependent stability criterion for neural networks is derived by using a simple integral inequality. The result is in terms of linear matrix inequalities and turn out to be equivalent to the existing result but include the least number of variables. This implies that some redundant variables in the existing stability criterion can be removed while maintaining the efficiency of the stability conditions. With the present stability condition, the computational burden is largely reduced. A numerical example is given to verify the effectiveness of the proposed criterion. © 2008 Springer-Verlag Berlin Heidelberg.