A physical memristor model for Pavlovian associative memory

作者：Jiale Lu, Haofeng Ran, Dirui Xie, Guangdong Zhou, Xiaofang Hu · 发表于：Chinese Physics B · 年份：2024 · DOI：10.1088/1674-1056/ad8b37 · 被引用次数：5 · 研究领域：Advanced Memory and Neural Computing、Neural Networks and Applications、Neural Networks Stability and Synchronization

Abstract Brain-inspired intelligence is considered to be a computational model with the most promising potential to overcome the shortcomings of the von Neumann architecture, making it a current research hotspot. Due to advantages such as nonvolatility, high density, low power consumption, and high response ratio, memristors are regarded as devices with promising applications in brain-inspired intelligence. This paper proposes a physical Ag/HfO x /FeO x /Pt memristor model. The Ag/HfO x /FeO x /Pt memristor is first fabricated using magnetron sputtering, and its internal principles and characteristics are then thoroughly analyzed. Furthermore, we construct a corresponding physical memristor model which achieves a simulation accuracy of up to 99.72% for the physical memristor. We design a fully functional Pavlovian associative memory circuit, realizing functions including generalization, primary differentiation, secondary differentiation, and forgetting. Finally, the circuit is validated through PSPICE simulation and analysis.