According to conventional memristive neural network theories, neurodynamic properties are
powerful tools for solving many problems in the areas of brain-like associative learning …

This paper considers the asymptotic and finite-time synchronization of drive-response
memristive neural networks (MNNs) with time-varying delays. It is known that the parameters …

In this paper, the issue of stability and stabilization for semi-Markov jump memristive neural
networks (SMJMNNs) with stochastic quantized sampled-data control (QSDC) law is …

In this article, we propose a novel chaotic neuron circuit with memristive neural synapses,
construct an architecture of memristive chaotic neural network (MCNN) and implement …

The research direction of this paper is passivity and passification of memristive recurrent
neural networks (MRNNs) with multi-proportional delays and impulse. Preparing for passive …

Due to the existence of time-varying chaotic disturbances in complex applications, the
chaotic synchronization of sensor systems becomes a tough issue in industry electronics …

The problem of finite-time synchronization for memristive neural networks (MNNs) with
proportional delay is considered. Since proportional delay is unbounded and different from …

This paper investigates the stability and stabilization of inertial memristive neural networks
(IMNNs) with discrete and unbounded distributed delays. The considered IMNNs are …

In this paper, the synchronization of memristor-based neural networks with time-varying
delays via pinning control is investigated. A novel pinning method is introduced to …

As an indispensable part of memristive synaptic weights, the switching jumps can induce
instability, oscillation or even chaos to the memristive network system. Based on the …