E. Miranda ; E. Piros ; F. L. Aguirre ; T. Kim ; P. Schreyer ; J. Gehrunger ; T. Schwarz ; T. Oster ; K. Hofmann ; J. Suñé ; C. Hochberger ; L. Alff (2024):
The role of the programming trajectory in the power dissipation dynamics and energy consumption of memristive devices.
In: IEEE Electron Device Letters, ISSN 0741-3106, New York, NY, IEEE,
DOI: https://doi.org/10.1109/LED.2024.3368146,
[Artikel]

Jonas Gehrunger ; Christian Hochberger (2023):
Design Space Exploration of Application Specific Number Formats Targeting an FPGA Implementation of SPICE.
In: 19th International Symposium on Applied Reconfigurable Computing, Cottbus, Germany, 27.-29.09.2023, In: Applied Reconfigurable Computing. Architectures, Tools, and Applications, 14251, S. 66-80, ISBN 978-3-031-42920-0, Springer Nature Switzerland,
DOI: https://doi.org/10.1007/978-3-031-42921-7_5,
[Konferenzveröffentlichung]

E. Miranda ; E. Piros ; F. L. Aguirre ; T. Kim ; P. Schreyer ; J. Gehrunger ; T. Oster ; K. Hofmann ; J. Suñé ; C. Hochberger ; L. Alff (2023):
Simulation of bipolar-type resistive switching devices using a recursive approach to the dynamic memdiode model.
In: IEEE Electron Device Letters, S. 1551-1554, ISSN 0741-3106, New York, NY, IEEE,
DOI: https://doi.org/10.1109/LED.2023.3298023,
[Artikel]

F. Aguirre ; E. Piros ; L. Alff ; C. Hochberger ; J. Gehrunger ; S. Petzold ; N. Kaiser ; E. Jalaguier ; E. Nolot ; C. Charpin-Nicolle ; T. Vogel ; L. Molina-Luna ; J. Suñé ; E. Miranda (2022):
Compact model for oxygen engineered Yttrium oxide-based resistive switching devices.
In: 2022 IEEE 22nd International Conference on Nanotechnology (NANO), Palma de Mallorca, Spain, 04.07.2022 - 08.07.2022, In: 2022 IEEE 22nd International Conference on Nanotechnology (NANO), S. 275-278, New York, NY, IEEE,
DOI: https://doi.org/10.1109/NANO54668.2022.9928654,
[Konferenzveröffentlichung]

Fernando Leonel Aguirre ; Eszter Piros ; Nico Kaiser ; Tobias Vogel ; Stephan Petzold ; Jonas Gehrunger ; Timo Oster ; Christian Hochberger ; Jordi Suñé ; Lambert Alff ; Enrique Miranda (2022):
Fast Fitting of the Dynamic Memdiode Model to the Conduction Characteristics of RRAM Devices Using Convolutional Neural Networks.
In: Micromachines, Darmstadt, MDPI, Universitäts- und Landesbibliothek Darmstadt,
DOI: https://doi.org/10.26083/tuprints-00022979,
[Online: https://tuprints.ulb.tu-darmstadt.de/22979],
[Artikel]