A comparative study of an Exponential Window function for Linear Drift Memristor Model

Chandra Prakash Singh, Vivek Pratap Singh, Harsh Ranjan, Abhishek Gupta, Saurabh Kumar Pandey

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A Memristive device is a two terminal electronic component that exhibits great potential for numerous applications in the area of non-volatile memories, mimicking synaptic characteristics, digital blocks, various analog circuit applications such as oscillators, programmable filters, modulation blocks, sensors, cellular neural networks, etc. In this article, we presented a generic exponential window function to describe the oxygen vacancy drifting in the linear drift model of the memristor. The proposed exponential window function significantly addresses boundary effect, boundary lock, and controllability problems and also provides different non-linearity according to the current direction. Two concern parameters are used in the presented window function which improves the controllability over the non-linearity of the memristive device which makes it more feasible for capturing resistive switching mechanism for futuristic memristive devices.

Original languageEnglish
Title of host publicationConference Proceedings - 2023 IEEE Silchar Subsection Conference, SILCON 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350314144
DOIs
StatePublished - 2023
Event2023 IEEE Silchar Subsection Conference, SILCON 2023 - Silchar, India
Duration: 3 Nov 20235 Nov 2023

Publication series

NameConference Proceedings - 2023 IEEE Silchar Subsection Conference, SILCON 2023

Conference

Conference2023 IEEE Silchar Subsection Conference, SILCON 2023
Country/TerritoryIndia
CitySilchar
Period3/11/235/11/23

Keywords

  • Boundary effect
  • Boundary Stick
  • Exponential Window function
  • Linear Drift Model
  • Memristor

Fingerprint

Dive into the research topics of 'A comparative study of an Exponential Window function for Linear Drift Memristor Model'. Together they form a unique fingerprint.

Cite this