A review for dynamic analysis and control of memristive neural networks

This paper provides a review of recent advances in memristive neural networks (MNNs), focusing on the issues of multi-stability, stabilization, and synchronization control. At first, the concepts of memristor and memristive neural networks are recalled by a short description of its background and several math models. On this basis, the corresponding control methods and research hotspots of MNNs are comprehensively discussed. Some engineering oriented phenomena in networked control are introduced and summarized, including multi-value storage and network-induced congestion, and so on. From these perspectives, the stability, stabilization, and synchronization control techniques of MNNs are discussed in detail. Furthermore, this paper introduces the latest advancements in fractional-order memristive neural networks (FMNNs) and thoroughly analyzes recent developments. Finally, some open issues and challenges are discussed to motivate the future research.