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Behavioral Modeling of Memristor-Based Rectifier Bridge

1
Department of Electrical Engineering Theory, Saint Petersburg Electrotechnical University “LETI”, 197376 St. Petersburg, Russia
2
Wuerth Elektronik eiSos GmbH, 74638 Waldenburg, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Luigi Fortuna
Appl. Sci. 2021, 11(7), 2908; https://doi.org/10.3390/app11072908
Received: 3 March 2021 / Revised: 21 March 2021 / Accepted: 23 March 2021 / Published: 24 March 2021
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
In electrical engineering, radio engineering, robotics, computing, control systems, etc., a lot of nonlinear devices are synthesized on the basis of a nanoelement named memristor that possesses a number of useful properties, such as passivity, nonlinearity, high variability of parameters, nonvolatility, compactness. The efficiency of this electric element has led to the emergence of many memristor technologies based on different physical principles and, as a result, to the occurrence of different mathematical models describing these principles. A general approach to the modeling of memristive devices is represented. The essence is to construct a behavioral model that approximates nonlinear mapping of the input signal set into the output signal set. The polynomials of split signals, which are adaptive to the class of input signals, are used. This adaptation leads to the model’s simplification important in practice. Multi-dimensional polynomials of split signals are built for the rectifier bridge at harmonic input signals. The modeling error is estimated in the mean-square norm. It is shown that the accuracy of the modeling is increased in the case of using the piecewise polynomial with split signals. View Full-Text
Keywords: behavioral modeling; nonlinear model; polynomial; nonlinear dynamic system; memristor; memristive device; rectifier bridge behavioral modeling; nonlinear model; polynomial; nonlinear dynamic system; memristor; memristive device; rectifier bridge
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MDPI and ACS Style

Solovyeva, E.; Schulze, S.; Harchuk, H. Behavioral Modeling of Memristor-Based Rectifier Bridge. Appl. Sci. 2021, 11, 2908. https://doi.org/10.3390/app11072908

AMA Style

Solovyeva E, Schulze S, Harchuk H. Behavioral Modeling of Memristor-Based Rectifier Bridge. Applied Sciences. 2021; 11(7):2908. https://doi.org/10.3390/app11072908

Chicago/Turabian Style

Solovyeva, Elena, Steffen Schulze, and Hanna Harchuk. 2021. "Behavioral Modeling of Memristor-Based Rectifier Bridge" Applied Sciences 11, no. 7: 2908. https://doi.org/10.3390/app11072908

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