Memristive Model for Synaptic Circuits

作者：Yang Zhang, Xiaoping Wang, Yi Li, Eby G. Friedman · 发表于：IEEE Transactions on Circuits & Systems II Express Briefs · 年份：2016 · DOI：10.1109/tcsii.2016.2605069 · 被引用次数：189 · 研究领域：Advanced Memory and Neural Computing、Neural dynamics and brain function、Neuroscience and Neural Engineering

As a promising alternative for next-generation memory, memristors provide several useful features such as high density, nonvolatility, low power, and good scalability as compared with conventional CMOS-based memories. In this brief, a voltage-controlled threshold memristive model is proposed, which is based on experimental data of memristive devices. Moreover, the model is more suitable for the design of memristor-based synaptic circuits as compared with other memristive models. The effects of memristance variations are considered in the proposed model to evaluate the behavior of memristive synapses within memristor-based neural networks.