In this paper, we propose new delay independent and dependent H∞ stability conditions for delayed neural networks with external disturbances and norm-bounded uncertainties. These conditions are presented to not only guarantee the asymptotical stability but also reduce the effect of external disturbance to an H∞ norm constraint. The proposed conditions are represented by linear matrix inequalities (LMIs). Optimal H∞ norm bounds are obtained easily by solving convex problems in terms of LMIs. The applicability of these conditions is illustrated by numerical examples.
- H analysis
- delayed neural networks
- linear matrix inequality (LMI)
ASJC Scopus subject areas
- Computer Science(all)