Abstract
Memristors, as fundamental passive circuit elements with non-volatile characteristics, have garnered significant interest for next-generation computing and storage systems. This paper evaluates memristor parameters using two well-established models: the Linear Ion Drift Model, the earliest representation of memristive behavior, and the Versatile Memristor Model (V-TEAM), an advanced framework capable of capturing a wide range of memristor characteristics [1]. By comparing these models, we analyze IV curves and hysteresis loops under varying voltage and frequency conditions. Furthermore, leveraging the VTEAM model [2], a memristor-based full adder circuit is designed and implemented for high-density, low-power logic applications. Highlighting advantages such as reduced circuit complexity, non-volatility, and energy efficiency, the proposed design positions memristor-based logic as a promising solution for neuromorphic and resistive computing systems. The insights from this study support the advancement of memristive devices in future memory and computing technologies.
| Original language | English |
|---|---|
| Title of host publication | 2025 2nd International Conference on Circuits, Power, and Intelligent Systems, CCPIS 2025 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331537791 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 2nd International Conference on Circuits, Power, and Intelligent Systems, CCPIS 2025 - Bhubaneswar, India Duration: 05-09-2025 → 07-09-2025 |
Publication series
| Name | 2025 2nd International Conference on Circuits, Power, and Intelligent Systems, CCPIS 2025 |
|---|
Conference
| Conference | 2nd International Conference on Circuits, Power, and Intelligent Systems, CCPIS 2025 |
|---|---|
| Country/Territory | India |
| City | Bhubaneswar |
| Period | 05-09-25 → 07-09-25 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Information Systems and Management
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
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