Modeling the Flux-Charge Relation of Memristor with Neural Network of Smooth Hinge Functions
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Date
2014-09
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ORCID
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Referee
Mark
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Společnost pro radioelektronické inženýrství
Abstract
The memristor was proposed to characterize the flux-charge relation. We propose the generalized flux-charge relation model of memristor with neural network of smooth hinge functions. There is effective identification algorithm for the neural network of smooth hinge functions. The representation capability of this model is theoretically guaranteed. Any functional flux-charge relation of a memristor can be approximated by the model. We also give application examples to show that the given model can approximate the flux-charge relation of existing piecewise linear memristor model, window function memristor model, and a physical memristor device.
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Citation
Radioengineering. 2014, vol. 23, č. 3, s. 939-943. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2014/14_03_0939_0943.pdf
http://www.radioeng.cz/fulltexts/2014/14_03_0939_0943.pdf
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Peer-reviewed
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en