Abstract
Memristive neurodynamic systems find many potential applications in mixed analog-digital multichip neurogrid and integrated photo-supercapacitor nanotube arrays. Analysis and design of memristive neurodynamic systems have attracted a large amount of research interest. In this study, some new neurodynamic approaches are proposed for stability analysis of delayed memristive neural networks. Some less conservative stability criteria are established by considering the memristor multiport effect, which is ignored in the previous literature. Numerical examples are given to demonstrate the effectiveness of these stability criteria.
Highlights
In recent years, memristive neurodynamic systems have become one of the most widely researched topics in the computing architecture enabled by memristors [ – ]
It is worth mention that using memristors as synaptic connections in neuromorphic electronic systems has been suggested with different neural architectures
5 Concluding remarks The memristive neurodynamic system exhibits well-characterized analog switching effects in electrical characteristics for devices formed by multiport architectures
Summary
Memristive neurodynamic systems have become one of the most widely researched topics in the computing architecture enabled by memristors [ – ]. We consider the global exponential stability and global asymptotical stability for a class of delayed memristive neural networks. The analytical method differs from those considered in most of the existing literature on qualitative analysis of memristive neurodynamic systems, where the memristor multiport effect is ignored.
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