Digital multiplier‐less implementation of high‐precision SDSP and synaptic strength‐based STDP

Abstract

Spiking neural networks (SNNs) can achieve lower latency and higher efficiency compared with traditional neural networks if they are implemented in dedicated neuromorphic hardware. In both biological and artificial spiking neuronal systems, synaptic modifications are the main mechanism for learning. Plastic synapses are thus the core component of neuromorphic hardware with on‐chip learning capability. Recently, several research groups have designed hardware architectures for modeling plasticity in SNNs for various applications. Follow Show more