11 citations · 12 across the 8 of their papers we have counts for
4 papers · 1 filter
Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
Arianna Rubino, Matteo Cartiglia, Melika Payvand +1
Mixed-signal neuromorphic systems represent a promising solution for solving extreme-edge computing tasks without relying on external computing resources. Their spiking neural netw…
Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits
Lyes Khacef, Philipp Klein, Matteo Cartiglia +3
Understanding how biological neural networks carry out learning using spike-based local plasticity mechanisms can lead to the development of powerful, energy-efficient, and adaptiv…
Online Detection of Vibration Anomalies Using Balanced Spiking Neural Networks
Nik Dennler, Germain Haessig, Matteo Cartiglia +1
Vibration patterns yield valuable information about the health state of a running machine, which is commonly exploited in predictive maintenance tasks for large industrial systems.…
An error-propagation spiking neural network compatible with neuromorphic processors
Matteo Cartiglia, Germain Haessig, Giacomo Indiveri
Spiking neural networks have shown great promise for the design of low-power sensory-processing and edge-computing hardware platforms. However, implementing on-chip learning algori…