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Cited by 163

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

A Boundary Condition-Based Approach to the Modeling of Memristor Nanostructures

Corinto, Fernando, Ascoli, Alon·2012·IEEE Transactions on Circuits and Systems I: Regular Papers

Abstract

A deep theoretical discussion proves that in Joglekar's and Biolek's models the memductance-flux relation of a memristor driven by a sign-varying voltage source may only exhibit single-valuedness and multi-valuedness respectively. This manuscript derives a novel boundary condition-based Model for memristor nanostructures. Unlike previous models, the proposed one allows for closed-form solutions. More importantly, subject to the nonlinear behavior under exam, this model enables a suitable tuning of boundary conditions, which may result in the detection of both single-valued and multi-valued memductance-flux relations under certain sign-varying inputs of interest. The large class of modeled dynamics include all behaviors reported in the legendary paper revealing the existence of memory-resistance at the nano scale.

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Metadata

Authors
Corinto, F., & Ascoli, A.
Venue
IEEE Transactions on Circuits and Systems I: Regular Papers
Published
2012-11
Volume
59
Issue
11
Pages
2713-2726
ISSN
  • 1549-8328 (ISSN-L)
  • 1558-0806
OpenAlex
W2059888459
Cited by
163
References
7
FWCI
14.24
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Boundary Condition-Based Approach to the Modeling of Memristor Nanostructures. https://app.cochat.ai/papers/10.1109/tcsi.2012.2190563
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Corinto, F., & Ascoli, A. (2012). A Boundary Condition-Based Approach to the Modeling of Memristor Nanostructures. IEEE Transactions on Circuits and Systems I: Regular Papers. https://doi.org/10.1109/tcsi.2012.2190563

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.