Abstract
This paper studies the passivity analysis of delayed neural networks (NNs) via novel integral inequality. First of all, an improved double integral inequality is proposed by virtue of the zero-qualities and some other analytical techniques Secondly, more information about time-delayed and neuron activation function vector are considered in constructing the augmented Lyapunov-Krasovskii functional (LKF). Leant on the several methods mentioned above, some less conservative conditions are obtained. In the end, some numerical examples are provided to show the effectiveness and superiority over the derived results.
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