Zobrazeno 1 - 10
of 277
pro vyhledávání: '"Gianluca Setti"'
Autor:
Fernando Aguirre, Abu Sebastian, Manuel Le Gallo, Wenhao Song, Tong Wang, J. Joshua Yang, Wei Lu, Meng-Fan Chang, Daniele Ielmini, Yuchao Yang, Adnan Mehonic, Anthony Kenyon, Marco A. Villena, Juan B. Roldán, Yuting Wu, Hung-Hsi Hsu, Nagarajan Raghavan, Jordi Suñé, Enrique Miranda, Ahmed Eltawil, Gianluca Setti, Kamilya Smagulova, Khaled N. Salama, Olga Krestinskaya, Xiaobing Yan, Kah-Wee Ang, Samarth Jain, Sifan Li, Osamah Alharbi, Sebastian Pazos, Mario Lanza
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-40 (2024)
Abstract Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL) techniques, which rely on networks of connected simple computing units operating in parallel. The low communication bandwidth between memory and proc
Externí odkaz:
https://doaj.org/article/2747dc5462eb47f38960b290c0cdbb9e
Autor:
Aijaz H. Lone, Arnab Ganguly, Hanrui Li, Nazek El-Atab, Gianluca Setti, Gobind Das, and Hossein Fariborzi
Publikováno v:
IEEE Access, Vol 12, Pp 149850-149860 (2024)
The exceptional properties of skyrmion devices, including their miniature size, topologically protected nature, and low current requirements, render them highly promising for energy-efficient neuromorphic computing applications. Examining the creatio
Externí odkaz:
https://doaj.org/article/e1ec57b469494abbbbbadb9fc956f67a
Publikováno v:
IEEE Access, Vol 8, Pp 205568-205589 (2020)
In recently published papers, an innovative analytical approach for the design of a class-E resonant dc-dc converter has been first proposed and further extended to many other class-E converter topologies. Its peculiarity is to be dimensionless and b
Externí odkaz:
https://doaj.org/article/304d525132124cb7a77359b5513c597c
Autor:
Carmine Paolino, Alessio Antolini, Francesco Zavalloni, Andrea Lico, Eleonora Franchi Scarselli, Mauro Mangia, Alex Marchioni, Fabio Pareschi, Gianluca Setti, Riccardo Rovatti, Mattia Luigi Torres, Marcella Carissimi, Marco Pasotti
Publikováno v:
Journal of Low Power Electronics and Applications, Vol 13, Iss 1, p 17 (2023)
Analog In-Memory computing (AIMC) is a novel paradigm looking for solutions to prevent the unnecessary transfer of data by distributing computation within memory elements. One such operation is matrix-vector multiplication (MVM), a workhorse of many
Externí odkaz:
https://doaj.org/article/9572963715af4224adc9983be52a773b
Publikováno v:
IEEE Access, Vol 7, Pp 83825-83838 (2019)
Resonant and quasi-resonant dc-dc converters have been introduced to increase the operating frequency of switching power converters, with advantages in terms of performance, cost, and/or size. In this paper, we focus on class-E resonant topologies, a
Externí odkaz:
https://doaj.org/article/1bb37857e662453ca4f85ea9664ec22d
EMI Reduction via Spread Spectrum in DC/DC Converters: State of the Art, Optimization, and Tradeoffs
Publikováno v:
IEEE Access, Vol 3, Pp 2857-2874 (2015)
Spread spectrum is a technique introduced for mitigating electromagnetic interference (EMI) problems in many class of circuits. In this paper, with particular emphasis on switching DC/DC converters, we consider the most common and most efficient know
Externí odkaz:
https://doaj.org/article/b11b787377e14a68b2cb71c3c8138474
Autor:
Gianluca Setti
Publikováno v:
IEEE Access, Vol 1, Pp 232-246 (2013)
This paper provides an overview of the main features of several bibliometric indicators which were proposed in the last few decades. Their pros and cons are highlighted and compared with the features of the well-known impact factor (IF) to show how a
Externí odkaz:
https://doaj.org/article/a53c10bd06524f74a3c435b498821d77
Autor:
Alessio Antolini, Carmine Paolino, Francesco Zavalloni, Andrea Lico, Eleonora Franchi Scarselli, Mauro Mangia, Fabio Pareschi, Gianluca Setti, Riccardo Rovatti, Mattia Luigi Torres, Marcella Carissimi, Marco Pasotti
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 13:395-407
Matrix-Vector Multiplications (MVMs) represent a heavy workload for both training and inference in Deep Neural Networks (DNNs) applications. Analog In-memory Computing (AIMC) systems based on Phase Change Memory (PCM) has been shown to be a valid com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11ada0cec13a2a0d4655f4b10b1524bb
https://doi.org/10.1109/jetcas.2023.3241750
https://doi.org/10.1109/jetcas.2023.3241750
Publikováno v:
IEEE Transactions on Cybernetics. 53:1324-1334
Applying chaos theory for secure digital communications is promising and it is well acknowledged that in such applications the underlying chaotic systems should be carefully chosen. However, the requirements imposed on the chaotic systems are usually
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4549c006fd6d57e2bb90b9284bde0e84
https://doi.org/10.1109/tcyb.2021.3129808
https://doi.org/10.1109/tcyb.2021.3129808
Autor:
Andriy Enttsel, Filippo Martinini, Alex Marchioni, Mauro Mangia, Riccardo Rovatti, Gianluca Setti
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::883a25505013176a1da9965f6b92b10a
https://doi.org/10.1109/icassp49357.2023.10095287
https://doi.org/10.1109/icassp49357.2023.10095287