Synaptic Resistors for Concurrent Inference and Learning with High Energy Efficiency
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Synaptic Resistors for Concurrent Inference and Learning with High Energy Efficiency
Authors
Keywords
-
Journal
ADVANCED MATERIALS
Volume -, Issue -, Pages 1808032
Publisher
Wiley
Online
2019-03-26
DOI
10.1002/adma.201808032
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Equivalent-accuracy accelerated neural-network training using analogue memory
- (2018) Stefano Ambrogio et al. NATURE
- Unsupervised Learning Using Charge-Trap Transistors
- (2017) Xuefeng Gu et al. IEEE ELECTRON DEVICE LETTERS
- Face classification using electronic synapses
- (2017) Peng Yao et al. Nature Communications
- Tuning the Fermi Level of TiO2 Electron Transport Layer through Europium Doping for Highly Efficient Perovskite Solar Cells
- (2017) Zhe Xu et al. Energy Technology
- Mastering the game of Go with deep neural networks and tree search
- (2016) David Silver et al. NATURE
- The chips are down for Moore’s law
- (2016) M. Mitchell Waldrop NATURE
- Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
- (2016) Zhongrui Wang et al. NATURE MATERIALS
- Training and operation of an integrated neuromorphic network based on metal-oxide memristors
- (2015) M. Prezioso et al. NATURE
- A million spiking-neuron integrated circuit with a scalable communication network and interface
- (2014) P. A. Merolla et al. SCIENCE
- Finding a roadmap to achieve large neuromorphic hardware systems
- (2013) Jennifer Hasler et al. Frontiers in Neuroscience
- A Carbon Nanotube Synapse with Dynamic Logic and Learning
- (2012) Kyunghyun Kim et al. ADVANCED MATERIALS
- Design, analysis and experimental evaluation of block based transformation in MFCC computation for speaker recognition
- (2011) Md. Sahidullah et al. SPEECH COMMUNICATION
- Ionic/Electronic Hybrid Materials Integrated in a Synaptic Transistor with Signal Processing and Learning Functions
- (2010) Qianxi Lai et al. ADVANCED MATERIALS
- The free-energy principle: a unified brain theory?
- (2010) Karl Friston NATURE REVIEWS NEUROSCIENCE
- High-yield of memory elements from carbon nanotube field-effect transistors with atomic layer deposited gate dielectric
- (2008) Marcus Rinkiö et al. NEW JOURNAL OF PHYSICS
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now