Zobrazeno 1 - 10
of 111
pro vyhledávání: '"Igor Aizenberg"'
Autor:
Igor Aizenberg, Alexander Vasko
Publikováno v:
Algorithms, Vol 17, Iss 8, p 361 (2024)
This paper presents a detailed analysis of a convolutional neural network based on multi-valued neurons (CNNMVN) and a fully connected multilayer neural network based on multi-valued neurons (MLMVN), employed here as a convolutional neural network in
Externí odkaz:
https://doaj.org/article/041e3b51e84940a6a04050c9fd1b3e65
Autor:
Carlos Alberto Iturrino Garcia, Marco Bindi, Fabio Corti, Antonio Luchetta, Francesco Grasso, Libero Paolucci, Maria Cristina Piccirilli, Igor Aizenberg
Publikováno v:
Energies, Vol 16, Iss 9, p 3627 (2023)
The main objective of this paper is to propose two innovative monitoring methods for electrical disturbances in low-voltage networks. The two approaches present a focus on the classification of voltage signals in the frequency domain using machine le
Externí odkaz:
https://doaj.org/article/aeceb9012de8461ab868be31dc381326
Autor:
Marco Bindi, Fabio Corti, Igor Aizenberg, Francesco Grasso, Gabriele Maria Lozito, Antonio Luchetta, Maria Cristina Piccirilli, Alberto Reatti
Publikováno v:
Algorithms, Vol 15, Iss 3, p 74 (2022)
In this paper, a monitoring method for DC-DC converters in photovoltaic applications is presented. The primary goal is to prevent catastrophic failures by detecting malfunctioning conditions during the operation of the electrical system. The proposed
Externí odkaz:
https://doaj.org/article/9a50a05d0b224cc0b9ecf932ef0c5f3f
Autor:
Igor Aizenberg, Riccardo Belardi, Marco Bindi, Francesco Grasso, Stefano Manetti, Antonio Luchetta, Maria Cristina Piccirilli
Publikováno v:
Energies, Vol 14, Iss 1, p 85 (2020)
A smart monitoring system capable of detecting and classifying the health conditions of MV (Medium Voltage) underground cables is presented in this work. Using the analysis technique proposed here, it is possible to prevent the occurrence of catastro
Externí odkaz:
https://doaj.org/article/ec073f03913048d1b29a8839000acc69
Publikováno v:
2022 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::896f8e554d5321da52741b0c4d87aaec
https://doi.org/10.1109/uemcon54665.2022.9965659
https://doi.org/10.1109/uemcon54665.2022.9965659
Autor:
Marco Bindi, Carlos Iturrino Garcia, Antonio Luchetta, Franceso Grasso, Maria Cristina Piccirilli, Libero Paolucci, Igor Aizenberg
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4684b9cadae9029f8c9f8779f1319f18
https://doi.org/10.1109/ijcnn55064.2022.9892536
https://doi.org/10.1109/ijcnn55064.2022.9892536
Autor:
Francesco Grasso, Riccardo Belardi, Marco Bindi, Stefano Manetti, Maria Cristina Piccirilli, Igor Aizenberg, Antonio Luchetta
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 5:488-498
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9afb9084057809b135c196c6d301899d
https://doi.org/10.25046/aj050458
https://doi.org/10.25046/aj050458
Autor:
Riccardo Belardi, Francesco Grasso, Marco Bindi, Igor Aizenberg, Stefano Manetti, Antonio Luchetta, Maria Cristina Piccirilli
Publikováno v:
Energies, Vol 14, Iss 85, p 85 (2021)
Energies; Volume 14; Issue 1; Pages: 85
Energies; Volume 14; Issue 1; Pages: 85
A smart monitoring system capable of detecting and classifying the health conditions of MV (Medium Voltage) underground cables is presented in this work. Using the analysis technique proposed here, it is possible to prevent the occurrence of catastro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43107cc411518e0b1ab7ca755c935e38
https://www.mdpi.com/1996-1073/14/1/85
https://www.mdpi.com/1996-1073/14/1/85
Autor:
Marco Bindi, Francesco Grasso, Antonio Luchetta, Maria Cristina Piccirilli, Riccardo Belardi, Igor Aizenberg, Stefano Manetti
Publikováno v:
Electronics, Vol 10, Iss 349, p 349 (2021)
Electronics
Volume 10
Issue 3
Electronics
Volume 10
Issue 3
In this paper, we present a new method designed to recognize single parametric faults in analog circuits. The technique follows a rigorous approach constituted by three sequential steps: calculating the testability and extracting the ambiguity groups
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8fd9ba08accd20045be14d508fb3c51
https://www.mdpi.com/2079-9292/10/3/349
https://www.mdpi.com/2079-9292/10/3/349
Autor:
Alexander Vasko, Igor Aizenberg
Publikováno v:
2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP).
In this paper, a convolutional neural network (CNN) based on multi-valued neurons (MVNs) with complex-valued weights is presented. Convolutional neural networks are known as one of the best tools for solving such problems as image and speech recognit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2820e7c2ce8194a95a6e9c0c4394da1
https://doi.org/10.1109/dsmp47368.2020.9204076
https://doi.org/10.1109/dsmp47368.2020.9204076