Low-power, adaptive neuromorphic systems : recent progress and future directions

• Main Authors: Basu, Arindam, Acharya, Jyotibdha, Karnik, Tanay, Liu, Huichu, Li, Hai, Seo, Jae-Sun, Song, Chang
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2019
• Subjects: Neuromorphics; Engineering::Electrical and electronic engineering; Hardware
• Online Access: https://hdl.handle.net/10356/106809; http://hdl.handle.net/10220/49651; http://dx.doi.org/10.1109/JETCAS.2018.2816339
• Institution: Nanyang Technological University

In this paper, we present a survey of recent works in developing neuromorphic or neuro-inspired hardware systems. In particular, we focus on those systems which can either learn from data in an unsupervised or online supervised manner. We present algorithms and architectures developed specially to s...