Analytical modeling of a Y2O3-based memristive system for synaptic applications. (26th May 2020)

• Record Type: Journal Article
• Authors: Kumar, Sanjay; Agrawal, Rajan; Das, Mangal; Kumar, Pawan; Mukherjee, Shaibal
• Is Part Of: Journal of physics. Volume 53:Number 30(2020)
• Publication Date: 2020-05-26
• Subjects: analytical modeling -- memristive -- Y2O3 -- synaptic applications; Physics -- Periodicals; 530
• DOI: 10.1088/1361-6463/ab810e
• Languages: English
• ISSNs: 0022-3727

Abstract

Abstract: Here, an analytical model for Y2 O3 -based memristive systems is presented, since a traditional model such as the Yakopcic model significantly deviates to capture the neuromorphic behavior for yttria-based memristive systems. On the one hand, the proposed model has high correlation with the reported experimental data and overcomes the shortcomings of the Yakopcic model in the form of a lack of non-linear behavior in the drift current at the device boundaries by introducing a new window function and state variable. On the other hand, the Yakopcic model depends upon the device threshold voltage parameters, while the proposed model is generic and remains independent of any pre-defined set of threshold voltage parameters. As a result, the proposed analytical model can be used in designing real-world applications based on the neuromorphic properties of yttria-based or any generic memristive systems.