Supervised local training of spiking neural networks on digital neuromorphic hardware
Artificial Neural Networks (ANNs) have gathered exponential attention across diverse domains in recent years [1]. However, ANN training suffers from high and inefficient energy consumption on modern computers based on the von Neumann architecture [2]. Spiking Neural Networks (SNNs) [3], when implemented on neuromorphic hardware [4, 5], have emerged as…