Advances in Memristor-Based Neural Networks
Weilin Xu, Jingjuan Wang, Xiaobing Yan
Abstract
The rapid development of artificial intelligence (AI), big data analytics, cloud computing, and Internet of Things applications expect the emerging memristor devices and their hardware systems to solve massive data calculation with low power consumption and small chip area. This paper provides an overview of memristor device characteristics, models, synapse circuits, and neural network applications, especially for artificial neural networks and spiking neural networks. It also provides research summaries, comparisons, limitations, challenges, and future work opportunities.
Topics & Concepts
MemristorComputer scienceArtificial neural networkBig dataArtificial intelligencePhysical neural networkCloud computingComputer architectureResistive random-access memoryData scienceTypes of artificial neural networksRecurrent neural networkEngineeringElectrical engineeringData miningVoltageOperating systemAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering