Winner-takes-all mechanism realized by memristive neural network-Reference-Cited by-同舟云学术

Winner-takes-all mechanism realized by memristive neural network

Published:2019-12-09 Issue:24 Volume:115 Page:243701
ISSN:0003-6951
Container-title:Applied Physics Letters
language:en
Short-container-title:Appl. Phys. Lett.

Author:

Wang J. J.¹^ORCID,Yu Q.¹,Hu S. G.¹,Liu Yanchen¹,Guo Rui¹,Chen T. P.²,Yin Y.³,Liu Y.¹

Affiliation:

1. State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu 610054, People's Republic of China

2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore

3. Graduate School of Engineering, Gunma University, 1-5-1Tenjin, Kiryu, Gunma 376-8515, Japan

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

AIP Publishing

Subject

Physics and Astronomy (miscellaneous)

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5120973

Reference20 articles.

1. Smart electronic skin having gesture recognition function by LSTM neural network

2. Realization of a Power-Efficient Transmitter Based on Integrated Artificial Neural Network

3. Study of Recall Time of Associative Memory in a Memristive Hopfield Neural Network

4. Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks

5. A high-storage capacity content-addressable memory and its learning algorithm

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