Energy Efficient Spiking Temporal Encoder Design for Neuromorphic Computing Systems

摘要: Neuromorphic computing hardware has undergone a rapid development and progress in the past few years. One of key components neuromorphic systems is neural encoder which transforms sensory information into spike trains. In this paper, both rate encoding temporal schemes are discussed. Two novel schemes, parallel iteration, presented. The power consumption been significantly reduced by combing iteration low sampling advanced complementary metal-oxide semiconductor (CMOS) nano-technology. Both simulation measurement results show accuracy efficiency proposed circuits. immediate applicability as general purpose input for reservoir system.