标题
Fully hardware-implemented memristor convolutional neural network
作者
关键词
-
出版物
NATURE
Volume 577, Issue 7792, Pages 641-646
出版商
Springer Science and Business Media LLC
发表日期
2020-01-30
DOI
10.1038/s41586-020-1942-4
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Memristive crossbar arrays for brain-inspired computing
- (2019) Qiangfei Xia et al. NATURE MATERIALS
- Phase-change heterostructure enables ultralow noise and drift for memory operation
- (2019) Keyuan Ding et al. SCIENCE
- Equivalent-accuracy accelerated neural-network training using analogue memory
- (2018) Stefano Ambrogio et al. NATURE
- SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations
- (2018) Shinhyun Choi et al. NATURE MATERIALS
- Neuro-Inspired Computing With Emerging Nonvolatile Memorys
- (2018) Shimeng Yu PROCEEDINGS OF THE IEEE
- Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
- (2018) Can Li et al. Nature Communications
- Sign backpropagation: An on-chip learning algorithm for analog RRAM neuromorphic computing systems
- (2018) Qingtian Zhang et al. NEURAL NETWORKS
- Memristor crossbar arrays with 6-nm half-pitch and 2-nm critical dimension
- (2018) Shuang Pi et al. Nature Nanotechnology
- Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks
- (2017) Yu-Hsin Chen et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
- Chaotic dynamics in nanoscale NbO2 Mott memristors for analogue computing
- (2017) Suhas Kumar et al. NATURE
- Sparse coding with memristor networks
- (2017) Patrick M. Sheridan et al. Nature Nanotechnology
- Face classification using electronic synapses
- (2017) Peng Yao et al. Nature Communications
- Improved Synaptic Behavior Under Identical Pulses Using AlOx/HfO2Bilayer RRAM Array for Neuromorphic Systems
- (2016) Jiyong Woo et al. IEEE ELECTRON DEVICE LETTERS
- Demonstration of Convolution Kernel Operation on Resistive Cross-Point Array
- (2016) Ligang Gao et al. IEEE ELECTRON DEVICE LETTERS
- Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses
- (2016) Alexander Serb et al. Nature Communications
- Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element
- (2015) Geoffrey W. Burr et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Training and operation of an integrated neuromorphic network based on metal-oxide memristors
- (2015) M. Prezioso et al. NATURE
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Memory leads the way to better computing
- (2015) H.-S. Philip Wong et al. Nature Nanotechnology
- A 3.1 mW 8b 1.2 GS/s Single-Channel Asynchronous SAR ADC With Alternate Comparators for Enhanced Speed in 32 nm Digital SOI CMOS
- (2013) Lukas Kull et al. IEEE JOURNAL OF SOLID-STATE CIRCUITS
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now