A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware

Arjun Rao, Philipp Plank, Andreas Wild, Wolfgang Maass

Abstract: Deep learning could be less energy intensive when implemented on spike-based neuromorphic chips. An approach inspired by a characteristic feature of biological neurons, the presence of slowly changing internal currents, is developed to emulate long short-term memory units in a sparse spiking regime for neuromorphic implementation.