Quantized Context Based LIF Neurons for Recurrent Spiking Neural Networks in 45nm

arXiv:2404.18066v1 Announce Type: cross
Abstract: In this study, we propose the first hardware implementation of a context-based recurrent spiking neural network (RSNN) emphasizing on integrating dual information streams within the neocortical pyramidal neurons specifically Context- Dependent Leaky Integrate and Fire (CLIF) neuron models, essential element in RSNN. We present a quantized version of the CLIF neuron (qCLIF), developed through a hardware-software codesign approach utilizing the sparse activity of RSNN. Implemented in a 45nm technology node, the qCLIF is compact (900um^2) …

abstract arxiv context cs.ai cs.ar cs.cv cs.ne element fire hardware implementation information network networks neural network neural networks neuron neurons q-bio.nc spiking neural network spiking neural networks study type