Stability Analysis for Neural Networks with Time-Variable Delays

In this paper, the stability of neural networks (NNs) with time-varying delays is investigated. By introducing a new Lyapunov-Krasovskii functional in virtue of the linearization of the model under investigation and considering the additional useful terms when estimating the upper bound of the derivative of Lyapunov functional, a new delay-dependent stability criterion is established in term of linear matrix inequality (LMI). Some numerical simulation examples aimed at justifying the theoretical results are also given.

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