no code implementations • 25 Oct 2023 • Simon F. Müller-Cleve, Fernando M. Quintana, Vittorio Fra, Pedro L. Galindo, Fernando Perez-Peña, Gianvito Urgese, Chiara Bartolozzi
Neuromorphic computing relies on spike-based, energy-efficient communication, inherently implying the need for conversion between real-valued (sensory) data and binary, sparse spiking representation.
1 code implementation • 19 Jan 2023 • Fernando M. Quintana, Fernando Perez-Peña, Pedro L. Galindo, Emre O. Neftci, Elisabetta Chicca, Lyes Khacef
We also show that when using local plasticity, threshold adaptation in spiking neurons and a recurrent topology are necessary to learn spatio-temporal patterns with a rich temporal structure.
