A physical memristor model for Pavlovian associative memory

doi:10.1088/1674-1056/ad8b37

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.

Keywords: memristor model Pavlovian associative memory circuit secondary differentiation

Received: 09 September 2024
Revised: 21 October 2024
Accepted manuscript online: 25 October 2024

PACS:	87.19.lv	(Learning and memory)
	84.30.Bv	(Circuit theory)
	84.30.-r	(Electronic circuits)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 62476230 and 61976246), the Natural Science Foundation of Chongqing (Grant No. CSTB2023NSCQ-MSX0018), and Fundamental Research Funds for the Central Universities (Grant No. SWUKR22046).

Corresponding Authors: Jiale Lu, Guangong Zhou, Xiaofang Hu
E-mail: krislu_111@163.com;zhougd@swu.edu.cn;huxf@swu.edu.cn

Cite this article:

Jiale Lu(卢家乐), Haofeng Ran(冉皓丰), Dirui Xie(谢頔睿), Guangong Zhou(周广东), and Xiaofang Hu(胡小方) A physical memristor model for Pavlovian associative memory 2025 Chin. Phys. B 34 018703

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