Energy-Efficient Neuromorphic Hardware. Design and Optimization of Brain-Inspired Computing Paradigms for Spiking Neural Networks

L'abstract è presente nell'allegato / the abstract is in the attachment

Grantor dc:publisher

Politecnico di Torino

Year dc:date

2025

Author dc:creator

• CARPEGNA, ALESSIO

Contributors dc:contributor

• DI CARLO, STEFANO
• SAVINO, ALESSANDRO

• Neuromorphic
• Spiking Neural Network
• LIF
• FPGA
• Neuromorphic accelerator
• Edge computing
• Artificial Intelligence
• Frugal AI
• Electronic Design Automation
• High-level synthesi
• Design Space Exploration
• Network Architecture Search
• Hyperparameters Optimization
• Continual Learning
• Latent Replay
• Time Compression
• Heart rate
• Wrist
• Biomedical monitoring
• Wearable devices
• Dementia
• Settore IINF-05/A - Sistemi di elaborazione delle informazioni

Statement dc:rights

• info:eu-repo/semantics/openAccess
• license:Creative commons
• license uri:http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language

eng

Identifier

http://dx.doi.org/10.13121/polito/porto/3004036
10.13121/polito/porto/3004036

OAI identifier oai:identifier

oai:iris.polito.it:11583/3004036