[PDF][PDF] Artificial neural network and its applications in the energy sector: an overview

DE Babatunde, A Anozie, J Omoleye - International Journal of Energy …, 2020 - zbw.eu
In order to realize the goal of optimal use of energy sources and cleaner environment at a
minimal cost, researchers; field professionals; and industrialists have identified the …

Daydreaming Hopfield Networks and their surprising effectiveness on correlated data

L Serricchio, D Bocchi, C Chilin, R Marino… - arXiv preprint arXiv …, 2024 - arxiv.org
To improve the storage capacity of the Hopfield model, we develop a version of the
dreaming algorithm that perpetually reinforces the patterns to be stored (as in the Hebb …

Repeated sequential learning increases memory capacity via effective decorrelation in a recurrent neural network

T Kurikawa, O Barak, K Kaneko - Physical Review Research, 2020 - APS
Memories in neural systems are shaped through the interplay of neural and learning
dynamics under external inputs. This interplay can result in either overwriting or …

Computation by natural systems

D Chu, M Prokopenko, JCJ Ray - Interface Focus, 2018 - royalsocietypublishing.org
Computation is a useful concept far beyond the disciplinary boundaries of computer science.
Perhaps the most important class of natural computers can be found in biological systems …

[PDF][PDF] Applicazione di un algoritmo d'apprendimento basato su sistemi fuori dall'equilibrio affidati di Genome Wide Association

G Castellani, DN Curti - core.ac.uk
Il fenomeno dell'apprendimento può essere studiato attraverso metodiche di Meccanica
Statistica unite alla cosiddetta Large Deviation Theory. In generale, l'apprendimento può …

[PDF][PDF] Statistical physics of neural systems.

F Gerace - 2018 - core.ac.uk
The ability of processing and storing information is considered a characteristic trait of
intelligent systems. In biological neural networks, learning is strongly believed to take place …