Search Results - "Giardino, Daniele"

Multi-Agent Reinforcement Learning: A Review of Challenges and Applications by Canese, Lorenzo, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Re, Marco, Spanò, Sergio

“…In this review, we present an analysis of the most used multi-agent reinforcement learning algorithms. Starting with the single-agent reinforcement learning…”
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A pseudo-softmax function for hardware-based high speed image classification by Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Nannarelli, Alberto, Re, Marco, Spanò, Sergio

“…In this work a novel architecture, named pseudo-softmax, to compute an approximated form of the softmax function is presented. This architecture can be…”
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An Efficient Hardware Implementation of Reinforcement Learning: The Q-Learning Algorithm by Spano, Sergio, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Matta, Marco, Nannarelli, Alberto, Re, Marco

“…In this paper we propose an efficient hardware architecture that implements the Q-Learning algorithm, suitable for real-time applications. Its main features…”
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Author Correction: A pseudo-softmax function for hardware-based high speed image classification by Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Nannarelli, Alberto, Re, Marco, Spanò, Sergio

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A Reinforcement Learning-Based QAM/PSK Symbol Synchronizer by Matta, Marco, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Nannarelli, Alberto, Re, Marco, Spano, Sergio

“…Machine Learning (ML) based on supervised and unsupervised learning models has been recently applied in the telecommunication field. However, such techniques…”
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An RNS-Based Initial Absolute Position Estimator for Electrical Encoders by Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Re, Marco, Nannarelli, Alberto, Spano, Sergio

“…In digital systems, the Residue Number System (RNS) represents an interesting alternative to the traditional two's complement representation. Its performance…”
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A Novel Digital Equalizer Based on RF Sampling Beyond GHz by Canese, Lorenzo, Carlo Cardarilli, Gian, Cesa, Riccardo la, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Re, Marco, Spano, Sergio

“…Hardware implementations represent the major challenges when digital signal processors for ultra-wideband (UWB) signals must be developed. Due to the…”
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Hardware Prototyping and Validation of a W-ΔDOR Digital Signal Processor by Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Matta, Marco, Re, Marco, Iess, Luciano, Cialfi, Fabio, De Angelis, Giorgio, Gelfusa, Dario, Pulcinelli, Ascanio Patrizio, Simone, Lorenzo

“…Microwave tracking, usually performed by on ground processing of the signals coming from a spacecraft, represents a crucial aspect in every deep-space mission…”
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An FPGA-based multi-agent Reinforcement Learning timing synchronizer by Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Re, Marco, Ricci, Andrea, Spanò, Sergio

“…In this paper we propose a Timing Recovery Loop for PSK and QAM modulations based on swarm Reinforcement Learning, suitable for FPGA implementation. We apply…”
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M-PSK Demodulator With Joint Carrier and Timing Recovery by Giardino, Daniele, Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Nannarelli, Alberto, Re, Marco, Spano, Sergio

“…In this brief, we propose a new digital receiver for Phase-Shift Keying (PSK) modulation based on the integration of the conventional digital Costas Loop…”
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"MR Q-Learning" Algorithm for Efficient Hardware Implementations by Carlo Cardarilli, Gian, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Natale, Dario, Re, Marco, Spano, Sergio

“…The maximum value finder block is one of the most critical parts in the hardware implementation of the Q-Learning Reinforcement Learning algorithm. To solve…”
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FPGA Implementation of Q-RTS for Real-Time Swarm Intelligence Systems by Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Matta, Marco, Nannarelli, Alberto, Re, Marco, Spano, Sergio

“…We propose an architectural blueprint to implement Q-RTS, Q-Learning Real-Time Swarm Reinforcement Learning algorithm, on FPGA. The design solution is built on…”
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A New Multilabel System for Automatic Music Emotion Recognition by Paolizzo, Fabio, Pichierri, Natalia, Giardino, Daniele, Matta, Marco, Casali, Daniele, Costantini, Giovanni

“…Achieving advancements in automatic recognition of emotions that music can induce require considering multiplicity and simultaneity of emotions. Comparison of…”
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A New Multilabel System for Automatic Music Emotion Recognition by Paolizzo, Fabio, Pichierri, Natalia, Casali, Daniele, Giardino, Daniele, Matta, Marco, Costantini, Giovanni

“…Achieving advancements in automatic recognition of emotions that music can induce require considering multiplicity and simultaneity of emotions. Comparison of…”
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A Q-Learning based PSK Symbol Synchronizer by Cardarilli, Gian Carlo, Di Nunzio, Luca, Fazzolari, Rocco, Giardino, Daniele, Matta, Marco, Re, Marco, Silvestri, Francesca, Spano, Sergio

“…Timing recovery loops are the state-of-the-art systems in telecommunication receivers with the purpose to recover the correct sampling time. They retrieve the…”
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Merged Carrier and Timing Recovery Loops QPSK Demodulator based on Iterative Learning Control by Cardarilli, Gian Carlo, Giardino, Daniele, Di Nunzio, Luca, Fazzolari, Rocco, Matta, Marco, Re, Marco, Silvestri, Francesca, Spano, Sergio

“…This paper presents a new architecture of QPSK demodulator with merged Carrier and Timing Recovery. It is based on Iterative Learning Control (ILC) and…”
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