Work

Research and Development of Parameter Extraction Approaches for Memristor Models

Year: 2021

Type: article

Abstract: Memristors are among the most promising devices for building neural processors and non-volatile memory. One circuit design stage involves modeling, which includes the option of memristor models. The most common approach is the use of compact models, the accuracy of which is often determined by the accuracy of their parameter extraction from experiment results. In this paper, a review of existing extraction methods was performed and new parameter extraction algorithms for an adaptive compact model were proposed. The effectiveness of the developed methods was confirmed for the volt-ampere characteristic of a memristor with a vertical structure: TiN/HfxAl1−xOy/HfO2/TiN.

Source: Micromachines

DOI: 10.3390/mi12101220

Authors: Dmitry Alexeevich Zhevnenko, Fedor Pavlovich Meshchaninov, Vladislav Sergeevich Kozhevnikov, Evgeniy Sergeevich Shamin, Oleg Alexandrovich Telminov, Evgeniy Sergeevich Gornev

Institutions: Moscow Institute of Physics and Technology, Research Institute of Molecular Electronics

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,944

Funder: Ministry of Science and Higher Education of the Russian Federation