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Found 2 papers, 1 papers with code
Hardware-aware training of models with synaptic delays for digital event-driven neuromorphic processors
In this work, we propose a framework to train and deploy, in digital neuromorphic hardware, highly performing spiking neural network models (SNNs) where apart from the synaptic weights, the per-synapse delays are also co-optimized.
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge.
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