Abstract
In this paper, the problem of delay-dependent stability of uncertain neural networks with time-varying delays is considered. The parameter uncertainties are time-varying and assumed to be bounded in magnitude. By constructing a new augmented Lyapunov functional, a delay-dependent stability criterion for the network is derived in terms of LMI (linear matrix inequality) which can be easily solved by various convex optimization algorithms. Three numerical examples are included to show the effectiveness of proposed criterion.
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