Global dissipativity of memristor-based neutral type inertial neural networks.
Neural Networks(2017)
摘要
The problem of global dissipativity for memristor-based inertial networks with time-varying delay of neutral type is investigated in this paper. Based on a proper variable substitution, the inertial system is transformed into a conventional system. Some sufficient criteria are established to ascertain the global dissipativity for the aforementioned inertial neural networks by employing analytical techniques and Lyapunov method. Meanwhile, the globally exponentially attractive sets and positive invariant sets are also presented here. Finally, numerical examples and simulations are given out to corroborate the effectiveness of obtained results.
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关键词
Inertial neural networks,Dissipativity,Neutral,Memristor
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