An improved fixed-time stabilization problem of delayed coupled memristor-based neural networks with pinning control and indefinite derivative approach

<abstract><p>In this brief, we propose a class of generalized memristor-based neural networks with nonlinear coupling. Based on the set-valued mapping theory, novel Lyapunov indefinite derivative and Memristor coupled (CMNNs) can achieve fixed-time stabilization (FTS) by designing proper pinning controller, which randomly controls small number neuron nodes. Different from traditional method, paper uses implementation method to deal non-autonomous network system coupling topology between different neurons. The obtain in fixed time requires fewer conditions. Moreover, stable setting estimation is given through few conditions, eliminate dependence initial value. Finally, give two numerical examples verify correctness our results.</p></abstract>