A multi-stable memristor and its application in a neural network
Hong , Qinghui
Nowadays, there is a lot of study on memristorbased systems with multistability. However, there is no study on memristor with multistability. This brief constructs a mathematical memristor model with multistability. The origin of the multi-stable dynamics is revealed using standard nonlinear theory as well as circuit and system theory. Moreover, the multi-stable memristor is applied to simulate a synaptic connection in a Hopﬁeld neural network. The memristive neural network successfully generates inﬁnitely many coexisting chaotic attractors unobserved in previous Hopﬁeld-type neural networks. The results are also conﬁrmed in analog circuits based on commercially available electronic elements.