In this paper, adaptive impedance control is developed for an-link robotic manipulator with
input saturation by employing neural networks. Both uncertainties and input saturation are …

This paper presents a complete solution for the hardware design of a memristor-based long
short-term memory (MLSTM) network. Throughout the design process, we fully consider the …

This paper investigates the synchronization problem of Takagi-Sugeno fuzzy memristive
neural networks (FMNNs) with mixed delays, in which the bounded distributed and …

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 …

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 global exponential synchronization of drive-response memristive
neural networks (MNNs) with heterogeneous time-varying delays. Because the parameters …

This paper is concerned with the finite-time synchronization (FTS) issue of switched coupled
neural networks with discontinuous or continuous activations. Based on the framework of …

This paper investigates the global asymptotic stability and stabilization of memristive neural
networks (MNNs) with communication delays via event-triggered sampling control. First …

In this paper, we investigate the synchronization problem on delayed memristive neural
networks (MNNs) with leakage delay and parameters mismatch via event-triggered control …

In this paper, to investigate the exponential synchronization of stochastic neural networks, a
new periodically intermittent discrete observation control (PIDOC) is first proposed. Different …