Zobrazeno 1 - 10
of 94
pro vyhledávání: '"neural network simulator"'
Publikováno v:
Frontiers in Neuroinformatics, Vol 15 (2021)
The Python Modular Neural Network Toolbox (PymoNNto) provides a versatile and adaptable Python-based framework to develop and investigate brain-inspired neural networks. In contrast to other commonly used simulators such as Brian2 and NEST, PymoNNto
Externí odkaz:
https://doaj.org/article/7be19feff7f246a88139d7a7bea6af8d
Publikováno v:
Frontiers in Neuroinformatics, Vol 15 (2021)
Due to the point-like nature of neuronal spiking, efficient neural network simulators often employ event-based simulation schemes for synapses. Yet many types of synaptic plasticity rely on the membrane potential of the postsynaptic cell as a third f
Externí odkaz:
https://doaj.org/article/749e386d369145efa10692e0720f073f
Autor:
Bruno Golosio, Gianmarco Tiddia, Chiara De Luca, Elena Pastorelli, Francesco Simula, Pier Stanislao Paolucci
Publikováno v:
Frontiers in Computational Neuroscience, Vol 15 (2021)
Over the past decade there has been a growing interest in the development of parallel hardware systems for simulating large-scale networks of spiking neurons. Compared to other highly-parallel systems, GPU-accelerated solutions have the advantage of
Externí odkaz:
https://doaj.org/article/cd03c19b9c094dbfac4ae22de66bec43
Autor:
Alejandro Humberto García Ruiz, Salvador Ibarra Martínez, José Antonio Castán Rocha, Jesús David Terán Villanueva, Julio Laria Menchaca, Mayra Guadalupe Treviño Berrones, Mirna Patricia Ponce Flores, Aurelio Alejandro Santiago Pineda
Publikováno v:
Symmetry, Vol 13, Iss 2, p 344 (2021)
Electricity is one of the most important resources for the growth and sustainability of the population. This paper assesses the energy consumption and user satisfaction of a simulated air conditioning system controlled with two different optimization
Externí odkaz:
https://doaj.org/article/bd7a532be7bf431abf4cbe6e66ec0a16
Autor:
Jan Hahne, David Dahmen, Jannis Schuecker, Andreas Frommer, Matthias Bolten, Moritz Helias, Markus Diesmann
Publikováno v:
Frontiers in Neuroinformatics, Vol 11 (2017)
Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that suppor
Externí odkaz:
https://doaj.org/article/d227892c35ec4dc5b7ae1c69987065f0
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Frontiers in Neuroinformatics, Vol 15 (2021)
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics
The Python Modular Neural Network Toolbox (PymoNNto) provides a versatile and adaptable Python-based framework to develop and investigate brain-inspired neural networks. In contrast to other commonly used simulators such as Brian2 and NEST, PymoNNto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::192cc342a002ae817bd6f0791d644d73
https://www.frontiersin.org/articles/10.3389/fninf.2021.715131/full
https://www.frontiersin.org/articles/10.3389/fninf.2021.715131/full
Autor:
Francesco Simula, Pierluigi Paolucci, Gianmarco Tiddia, E. Pastorelli, Bruno Golosio, Chiara De Luca
Publikováno v:
Frontiers in Computational Neuroscience
Frontiers in Computational Neuroscience, Vol 15 (2021)
Frontiers in Computational Neuroscience, Vol 15 (2021)
Over the past decade there has been a growing interest in the development of parallel hardware systems for simulating large-scale networks of spiking neurons. Compared to other highly-parallel systems, GPU-accelerated solutions have the advantage of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abe48c32e0ee3d41c4d01dbe1ada3261
Autor:
Beatriz Nistal-Nuño
Publikováno v:
Einstein (São Paulo), Volume: 18, Article number: eAO5480, Published: 20 NOV 2020
einstein (São Paulo) v.18 2020
Einstein (São Paulo)
Instituto Israelita de Ensino e Pesquisa Albert Einstein (IIEPAE)
instacron:IIEPAE
Einstein
Einstein (São Paulo), Vol 18 (2020)
einstein (São Paulo) v.18 2020
Einstein (São Paulo)
Instituto Israelita de Ensino e Pesquisa Albert Einstein (IIEPAE)
instacron:IIEPAE
Einstein
Einstein (São Paulo), Vol 18 (2020)
Objective: To propose a preliminary artificial intelligence model, based on artificial neural networks, for predicting the risk of nosocomial infection at intensive care units. Methods: An artificial neural network is designed that employs supervised
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::07b7e019a24488b0f282ed58397821ce
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-45082020000100282&lng=en&tlng=en
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1679-45082020000100282&lng=en&tlng=en
Autor:
Golosio, Bruno, De Luca, Chiara, Pastorelli, Elena, Simula, Francesco, Tiddia, Gianmarco, Paolucci, Pier Stanislao
of oral presentation at NEST Conference 2020, 29-30 June 2020, p. 7, https://indico-jsc.fz-juelich.de/event/115/
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f57be87aea2754fb331cbc4ed6abb02