Modeling of Memristors under Periodic Signals of Different Parameters
In this paper, the problem of modeling memristors is studied. Two types of memristors with carbon and tungsten doping fabricated by the Knowm Inc. are tested. The memristors have been examined with either sinusoidal or triangle voltage wave periodic excitation. Some different frequencies, amplitudes...
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/54abe90ef3024ab2bc3fa85a57c0c3ef |
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| Sumario: | In this paper, the problem of modeling memristors is studied. Two types of memristors with carbon and tungsten doping fabricated by the Knowm Inc. are tested. The memristors have been examined with either sinusoidal or triangle voltage wave periodic excitation. Some different frequencies, amplitudes and signal shapes have been applied. The collected data have been averaged and subjected to high frequency filtering. The quality of measurement data has also been discussed. The averaged measurement has been modeled using three popular memristor models: Strukov, Biolek and VTEAM. Some additional feathers to the considered models have been proposed and tested. Memristor is usually modeled by a set of algebraic-differential equations which link both electrical values (i.e., voltage and current) and the internal variable(s) responsible for the element dynamics. The interior-point with box constrains optimization method has been used to obtain the optimal parameters of the memristor model that fit best to the collected data. The results of the optimization process have been discussed and compared. The sensitivity to the different frequency range has been also examined and reviewed. Some conclusions and future work ideas have been postulated. |
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