Abstract: This paper is concerned with the stability problem
with two additive time-varying delay components. By choosing one
augmented Lyapunov-Krasovskii functional, using some new zero
equalities, and combining linear matrix inequalities (LMI)
techniques, two new sufficient criteria ensuring the global stability
asymptotic stability of DNNs is obtained. These stability criteria are
present in terms of linear matrix inequalities and can be easily
checked. Finally, some examples are showed to demonstrate the
effectiveness and less conservatism of the proposed method.
Abstract: This paper studies the problem of stability criteria
for neural networks with two additive time-varying delays.A new
Lyapunov-Krasovskii function is constructed and some new delay
dependent stability criterias are derived in the terms of linear
matrix inequalities(LMI), zero equalities and reciprocally convex
approach.The several stability criterion proposed in this paper is
simpler and effective. Finally,numerical examples are provided to
demonstrate the feasibility and effectiveness of our results.