Scalable Integrated Active Inference Neurons for Ultra-Low-Power On-Chip Edge Learning

Scaling of an existent ultra-low power hardware for active inference neuron, upgrading the number of synapses to 400. Implementation on MATLAB to simulate a SNN to classify MNIST dataset.