| Literature DB >> 30422812 |
Chul-Heung Kim, Suhwan Lim, Sung Yun Woo, Won-Mook Kang, Young-Tak Seo, Sung-Tae Lee, Soochang Lee, Dongseok Kwon, Seongbin Oh, Yoohyun Noh, Hyeongsu Kim, Jangsaeng Kim, Jong-Ho Bae, Jong-Ho Lee.
Abstract
In this paper, we reviewed the recent trends on neuromorphic computing using emerging memory technologies. Two representative learning algorithms used to implement a hardware-based neural network are described as a bio-inspired learning algorithm and software-based learning algorithm, in particular back-propagation. The requirements of the synaptic device to apply each algorithm were analyzed. Then, we reviewed the research trends of synaptic devices to implement an artificial neural network.Year: 2018 PMID: 30422812 DOI: 10.1088/1361-6528/aae975
Source DB: PubMed Journal: Nanotechnology ISSN: 0957-4484 Impact factor: 3.874