標題: | Interchangeable Hebbian and Anti-Hebbian STDP Applied to Supervised Learning in Spiking Neural Network |
作者: | Chang, Che-Chia Chen, Pin-Chun Hudec, Boris Liu, Po-Tsun Hou, Tuo-Hung 電子工程學系及電子研究所 光電工程學系 Department of Electronics Engineering and Institute of Electronics Department of Photonics |
公開日期: | 1-一月-2018 |
摘要: | This work provides a complete framework, including device, architecture, and algorithm, for implementing bio-inspired supervised spiking neural networks (SNNs) on hardware. An analog synapse with atypical dual bipolar resistive-switching (D-BRS) modes demonstrates interchangeable Hebbian spiking-timing-dependent plasticity (STDP) and anti-Hebbian STDP, and it is capable of implementing supervised ReSuMe SNNs in crossbar arrays. By using an "exchange" update scheme, accurate supervised learning (similar to 96% for MNIST) is achieved in a compact network. |
URI: | http://hdl.handle.net/11536/151104 |
ISSN: | 2380-9248 |
期刊: | 2018 IEEE INTERNATIONAL ELECTRON DEVICES MEETING (IEDM) |
顯示於類別: | 會議論文 |