Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Luca Di nunzio"'
Autor:
Lorenzo Canese, Gian Carlo Cardarilli, Riccardo la Cesa, Luca Di Nunzio, Rocco Fazzolari, Daniele Giardino, Marco Re, Sergio Spano
Publikováno v:
IEEE Access, Vol 12, Pp 92560-92572 (2024)
Hardware implementations represent the major challenges when digital signal processors for ultra-wideband (UWB) signals must be developed. Due to the limitation of the maximum clock rate in digital devices, systems with high sampling rates (above GHz
Externí odkaz:
https://doaj.org/article/d12e704da9d14109a5c21878b9b76b97
Autor:
Lorenzo Canese, Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Marco Re, Sergio Spanò
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract This paper proposes DQ-RTS, a novel decentralized Multi-Agent Reinforcement Learning algorithm designed to address challenges posed by non-ideal communication and a varying number of agents in distributed environments. DQ-RTS incorporates an
Externí odkaz:
https://doaj.org/article/6395a4506cfd4295970d589f66104e77
Design Space Exploration for Edge Machine Learning Featured by MathWorks FPGA DL Processor: A Survey
Autor:
Stefano Bertazzoni, Lorenzo Canese, Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Marco Re, Sergio Spano
Publikováno v:
IEEE Access, Vol 12, Pp 9418-9439 (2024)
This paper proposes a Design Space Exploration for Edge machine learning through the utilization of the novel MathWorks FPGA Deep Learning Processor IP, featured in the HDL Deep Learning toolbox. With the ever-increasing demand for real-time machine
Externí odkaz:
https://doaj.org/article/154825a88684484eaaaf5bb2425c3f6a
Autor:
Paweł Kowol, Pawel Nowak, Luca Di Nunzio, Gian Carlo Cardarilli, Giacomo Capizzi, Grazia Lo Sciuto
Publikováno v:
Applied System Innovation, Vol 7, Iss 3, p 37 (2024)
In this work, an organ pipe instrument with a mechatronic control system including the Passive Haptic Feedback technology is implemented. The test bed consists of a motorized positioning stage mounted to a brace that is attached to a bridge on a plat
Externí odkaz:
https://doaj.org/article/aa1a0f37b164439494d0422c34947b6b
Autor:
Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Daniele Giardino, Marco Re, Alberto Nannarelli, Sergio Spano
Publikováno v:
IEEE Access, Vol 11, Pp 98586-98595 (2023)
In digital systems, the Residue Number System (RNS) represents an interesting alternative to the traditional two’s complement representation. Its performance and low-power properties have attracted significant research interest over the years. In t
Externí odkaz:
https://doaj.org/article/a9f881b779a547f89c263bb080f9d9d8
Autor:
Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Daniele Giardino, Alberto Nannarelli, Marco Re, Sergio Spanò
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract In this work a novel architecture, named pseudo-softmax, to compute an approximated form of the softmax function is presented. This architecture can be fruitfully used in the last layer of Neural Networks and Convolutional Neural Networks fo
Externí odkaz:
https://doaj.org/article/7fd239c516c54de8b74b325a8777bbfd
Autor:
Lorenzo Canese, Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Hamed Famil Ghadakchi, Marco Re, Sergio Spanò
Publikováno v:
Sensors, Vol 22, Iss 22, p 8830 (2022)
Traffic sign detection systems constitute a key component in trending real-world applications such as autonomous driving and driver safety and assistance. In recent years, many learning systems have been used to help detect traffic signs more accurat
Externí odkaz:
https://doaj.org/article/e8ddb9426685480d96d7cb19b03884bb
Autor:
Sergio Spano, Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Daniele Giardino, Marco Matta, Alberto Nannarelli, Marco Re
Publikováno v:
IEEE Access, Vol 7, Pp 186340-186351 (2019)
In this paper we propose an efficient hardware architecture that implements the Q-Learning algorithm, suitable for real-time applications. Its main features are low-power, high throughput and limited hardware resources. We also propose a technique ba
Externí odkaz:
https://doaj.org/article/f1701f938224454db48a67f74210b57d
Autor:
Marco Matta, Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Daniele Giardino, Alberto Nannarelli, Marco Re, Sergio Spano
Publikováno v:
IEEE Access, Vol 7, Pp 124147-124157 (2019)
Machine Learning (ML) based on supervised and unsupervised learning models has been recently applied in the telecommunication field. However, such techniques rely on application-specific large datasets and the performance deteriorates if the statisti
Externí odkaz:
https://doaj.org/article/52c83e439292474382c3dc74e78b62d0
Autor:
Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Daniele Giardino, Alberto Nannarelli, Marco Re, Sergio Spanò
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-2 (2021)
Externí odkaz:
https://doaj.org/article/d4c7081cfe924628802e14077928617c