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Alessandro Salvini
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2020 – today
- 2025
- [j8]Sergi Abadal
, Pablo Galván, Alberto Mármol, Nadia Mammone
Graph neural networks for electroencephalogram analysis: Alzheimer's disease and epilepsy use cases. Neural Networks 181: 106792 (2025) - 2020
- [j7]Gabriele Maria Lozito
Swarm intelligence based approach for efficient training of regressive neural networks. Neural Comput. Appl. 32(14): 10693-10704 (2020)
2010 – 2019
- 2019
- [c11]Gabriele Maria Lozito, Valentina Lucaferri
Parallel Algorithm Based on Singular Value Decomposition for High Performance Training of Neural Networks. ICCS (5) 2019: 581-587 - [c10]Valentina Lucaferri
A novel method for dynamic battery model identification based on CFSO. PRIME 2019: 57-60 - [c9]Antonino Laudani
Numerical Dynamic Modeling and Analysis of DC-DC Converters for Photovoltaic Applications. RTSI 2019: 389-393 - 2018
- [c8]Paolo Di Barba, Maria Evelina Mognaschi, Gabriele Maria Lozito, Alessandro Salvini
The Benchmark TEAM Problem for Multi-Objective Optimization Solved with CFSO. RTSI 2018: 1-5 - 2017
- [j6]Ermanno Cardelli, Antonio Faba, Antonino Laudani, Simone Quondam Antonio, Francesco Riganti Fulginei, Alessandro Salvini:
Computer Modeling of Nickel-Iron Alloy in Power Electronics Applications. IEEE Trans. Ind. Electron. 64(3): 2494-2501 (2017) - [j5]Alberto Oliveri
Two FPGA-Oriented High-Speed Irradiance Virtual Sensors for Photovoltaic Plants. IEEE Trans. Ind. Informatics 13(1): 157-165 (2017) - [c7]Antonino Laudani
An analytical approach for maximum power point calculation for photovoltaic system. ECCTD 2017: 1-4 - 2016
- [c6]Antonino Laudani
Modeling dynamic hysteresis through Fully Connected Cascade neural networks. RTSI 2016: 1-5 - [c5]Antonino Laudani
FEM model identification for a vector hysteresis workbench. RTSI 2016: 1-5 - 2015
- [j4]Antonino Laudani
On Training Efficiency and Computational Costs of a Feed Forward Neural Network: A Review. Comput. Intell. Neurosci. 2015: 818243:1-818243:13 (2015) - [c4]Francesco Riganti Fulginei, Gabriele Maria Lozito, Stefano Gaiotto, Alessandro Salvini
Improving the Jiles-Atherton model by introducing a full dynamic dependence of parameters. RTSI 2015: 161-165 - 2014
- [j3]Antonino Laudani
Swarm/flock optimization algorithms as continuous dynamic systems. Appl. Math. Comput. 243: 670-683 (2014) - [j2]Fernando Mancilla-David, Francesco Riganti Fulginei
A Neural Network-Based Low-Cost Solar Irradiance Sensor. IEEE Trans. Instrum. Meas. 63(3): 583-591 (2014) - [c3]Antonino Laudani, Gabriele Maria Lozito, Martina Radicioni
Model Identification for Photovoltaic Panels Using Neural Networks. IJCCI (NCTA) 2014: 130-137 - [c2]Antonino Laudani
An Efficient Architecture for Floating Point Based MISO Neural Neworks on FPGA. UKSim 2014: 12-17 - 2013
- [j1]Maurizio Schmid
SVM versus MAP on Accelerometer Data to Distinguish among Locomotor Activities Executed at Different Speeds. Comput. Math. Methods Medicine 2013: 343084:1-343084:7 (2013) - [c1]Antonino Laudani
Closed Forms for the Fully-Connected Continuous Flock of Starlings Optimization Algorithm. UKSim 2013: 45-50 - 2011
- [p1]Francesco Riganti Fulginei
The Flock of Starlings Optimization: Influence of Topological Rules on the Collective Behavior of Swarm Intelligence. Computational Methods for the Innovative Design of Electrical Devices 2011: 129-145
Coauthor Index
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