Asymptotic stability on a class of nonlinear multi-delay neutral equations

This work gives an improved criterion for asymptotical stability of a class of neural networks described by multidelay neutral differential equations. By introducing suitable Lyapunov-Krasovskii functional, a delay dependent criterion which not only depends on the discrete delays but also on the neutral delay is presented. This paper has also broken away from the assumption of 0 <; |α| <; 1, which is used in the operator D in. The sufficient condition is expressed in terms of linear matrix inequality. The criterion can be solved by various efficient convex optimization algorithms. In the end of the work, utilized Matlab toolbox, the numerical example is presented to illustrate feasibility of the criterion given in the work.