CAMEM: A Computationally-Efficient and Accurate Memristive Model With Experimental Verification

• Published in: IEEE transactions on nanotechnology Vol. 18; pp. 1040 - 1049
• Main Authors: Hajri, Basma, Mansour, Mohammad M., Chehab, Ali, Aziza, Hassen
• Format: Journal Article
• Language: English
• Published: New York IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Accuracy; Circuit design; compact model; Computational efficiency; Computational modeling; Computer simulation; Engineering Sciences; experimental validation; Integrated circuit modeling; Mathematical model; Memory devices; Memristive models; Memristors; Micro and nanotechnologies; Microelectronics; Numerical models; Program verification (computers); resistive random access memory (RRAM); Simulators; SPICE
• ISSN: 1536-125X; 1941-0085
• DOI: 10.1109/TNANO.2019.2945985

When using memristive devices at the circuit level, a simple, accurate, and computationally efficient model is critically required to predict the performance of the circuit. Various memristive device models have been developed in the literature; however, most of them suffer from high complexity, low accuracy, or low computational efficiency. In this paper, a novel model for memristive devices for use at the circuit level is proposed. The proposed model is compact, sufficiently simple, computationally efficient, and compatible with popular circuit simulators. Moreover, the model meets circuit designers' requirements in terms of accuracy to explore new memristor-based design architectures. An experimental validation of the model is also provided.