神经形态工程学
MNIST数据库
人工神经网络
可穿戴计算机
计算机科学
材料科学
可穿戴技术
弯曲
晶体管
织物
突触
人工智能
纳米技术
电气工程
嵌入式系统
神经科学
工程类
复合材料
电压
生物
作者
Seonggil Ham,Minji Kang,Seonghoon Jang,Jingon Jang,Sanghyeon Choi,Tae‐Wook Kim,Gunuk Wang
出处
期刊:Science Advances
[American Association for the Advancement of Science]
日期:2020-07-10
卷期号:6 (28)
被引量:144
标识
DOI:10.1126/sciadv.aba1178
摘要
One-dimensional (1D) devices are becoming the most desirable format for wearable electronic technology because they can be easily woven into electronic (e-) textile(s) with versatile functional units while maintaining their inherent features under mechanical stress. In this study, we designed 1D fiber-shaped multi-synapses comprising ferroelectric organic transistors fabricated on a 100-μm Ag wire and used them as multisynaptic channels in an e-textile neural network for wearable neuromorphic applications. The device mimics diverse synaptic functions with excellent reliability even under 6000 repeated input stimuli and mechanical bending stress. Various NOR-type textile arrays are formed simply by cross-pointing 1D synapses with Ag wires, where each output from individual synapse can be integrated and propagated without undesired leakage. Notably, the 1D multi-synapses achieved up to ~90 and ~70% recognition accuracy for MNIST and electrocardiogram patterns, respectively, even in a single-layer neural network, and almost maintained regardless of the bending conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI