Zobrazeno 1 - 10
of 170
pro vyhledávání: '"Ch. Wenger"'
Autor:
V. Milo, C. Zambelli, P. Olivo, E. Pérez, M. K. Mahadevaiah, O. G. Ossorio, Ch. Wenger, D. Ielmini
Publikováno v:
APL Materials, Vol 7, Iss 8, Pp 081120-081120-10 (2019)
Training and recognition with neural networks generally require high throughput, high energy efficiency, and scalable circuits to enable artificial intelligence tasks to be operated at the edge, i.e., in battery-powered portable devices and other lim
Externí odkaz:
https://doaj.org/article/e4793824ffde4fd3b3885eb22cbe4674
Publikováno v:
2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO).
Autor:
Eduardo Perez, Martin Ziegler, Mamathamba Kalishettyhalli Mahadevaiah, Ch. Wenger, Finn Zahari, Hermann Kohlstedt, I. Beckers
Publikováno v:
IEEE Electron Device Letters. 40:639-642
Based on the inherent stochasticity of CMOS-integrated HfO2-based resistive random access memory (RRAM) devices, a new learning algorithm for neuro-morphic systems is presented. For this purpose, the device-to-device variability of CMOS-integrated 4-
Publikováno v:
Microelectronic Engineering. 178:1-4
The impact of temperature during the forming operation on the electrical cells performance and the post-programming stability were evaluated in amorphous and polycrystalline HfO2-based arrays. Forming (between 40 and 150C), reset and set (at room tem
Autor:
Christian Acal, Juan Bautista Roldán, Eduardo Perez, Ana M. Aguilera, D. Maldonado, Francisco Jiménez-Molinos, Ch. Wenger, F. J. Alonso, Juan Eloy Ruiz-Castro
In order to study the device-to-device and cycle-to-cycle variability of switching voltages in 4-kbit RRAM arrays, an alternative statistical approach has been adopted by using experimental data collected from a batch of 128 devices switched along 20
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85546e588977b394aa26c04d88981b17
https://doi.org/10.1016/j.mee.2019.05.004
https://doi.org/10.1016/j.mee.2019.05.004
Autor:
Martin Ziegler, Mamathamba Kalishettyhalli Mahadevaiah, Hermann Kohlstedt, Cristian Zambelli, Finn Zahari, Piero Olivo, Alessandro Grossi, Ch. Wenger, Eduardo Perez
Publikováno v:
IRPS
CMOS integrated 4kbit 1T-1R memristive devices were examined in terms of device-to-device and pulse number dependent variability for the use in neuromorphic systems. Based on the variability of polycrystalline HfO2 based Resistive Random Access Memor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f56360d0647620e7f87c64a06bd7a94
http://hdl.handle.net/11392/2407283
http://hdl.handle.net/11392/2407283
Autor:
Daniele Ielmini, Cristian Zambelli, Ch. Wenger, Piero Olivo, Valerio Milo, Eduardo Perez, Oscar G. Ossorio
Publikováno v:
ESSDERC 2019-49th European Solid-State Device Research Conference (ESSDERC)
ESSDERC
UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname
UVaDOC: Repositorio Documental de la Universidad de Valladolid
Universidad de Valladolid
ESSDERC
UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname
UVaDOC: Repositorio Documental de la Universidad de Valladolid
Universidad de Valladolid
Producción Científica
Recently, artificial intelligence reached impressive milestones in many machine learning tasks such as the recognition of faces, objects, and speech. These achievements have been mostly demonstrated in software running on
Recently, artificial intelligence reached impressive milestones in many machine learning tasks such as the recognition of faces, objects, and speech. These achievements have been mostly demonstrated in software running on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87572b1fe851c8b9c06f9b1bed2d7c46
http://hdl.handle.net/11311/1127733
http://hdl.handle.net/11311/1127733
Autor:
Oscar G. Ossorio, Daniele Ielmini, Cristian Zambelli, Ch. Wenger, Mamathamba Kalishettyhalli Mahadevaiah, Piero Olivo, Eduardo Perez, Valerio Milo
Publikováno v:
APL Materials
UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname
APL Materials, Vol 7, Iss 8, Pp 081120-081120-10 (2019)
UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname
APL Materials, Vol 7, Iss 8, Pp 081120-081120-10 (2019)
Producción Científica
Training and recognition with neural networks generally require high throughput, high energy efficiency, and scalable circuits to enable artificial intelligence tasks to be operated at the edge, i.e., in battery-powered p
Training and recognition with neural networks generally require high throughput, high energy efficiency, and scalable circuits to enable artificial intelligence tasks to be operated at the edge, i.e., in battery-powered p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a62c54b73d51a8fae03de52f2eba32b5
http://hdl.handle.net/11311/1111812
http://hdl.handle.net/11311/1111812
Autor:
Alessandro Grossi, Cristian Zambelli, Mamathamba Kalishettyhalli Mahadevaiah, Eduardo Perez, Ch. Wenger, Piero Olivo
Publikováno v:
2018 IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP).
In this paper, the impact of the forming temperature on the reliability of Hafnium-based RRAM arrays has been investigated. A wide range of high temperatures from 25 °C to 150 °C during the forming operations have been applied. Endurance and retent
Publikováno v:
The Analyst. 140:3262-3272
In this report we propose a sensor architecture and a corresponding read-out technique on silicon for the detection of dynamic capacitance change. This approach can be applied to rapid particle counting and single particle sensing in a fluidic system