A multi-stable memristor and its application in a neural network

Hairong Lin, Chunhua Wang, Qinghui Hong , Yichuang Sun

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)
59 Downloads (Pure)

Abstract

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.
Original languageEnglish
Number of pages5
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
Early online date8 Jun 2020
DOIs
Publication statusE-pub ahead of print - 8 Jun 2020

Fingerprint

Dive into the research topics of 'A multi-stable memristor and its application in a neural network'. Together they form a unique fingerprint.

Cite this