Passivity analysis of memristive neural networks with different memductance functions

Memristive neural networks have captured the attention of physicists, biologists, ecologists, economists and social scientists. In this paper, we formulate and investigate a class of memristive neural networks with two different types of memductance functions. Some succinct criteria in terms of linear matrix inequalities for the passivity are proposed. Meanwhile, based on the derived criteria, some stability criterion are obtained for the memristive neural networks. These theoretical analysis can characterize the fundamental electrical properties of memristive systems and provide convenience for applications.