A CMOS-memristive self-learning neural network for pattern classification applications-Reference-Cited by-同舟云学术

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A CMOS-memristive self-learning neural network for pattern classification applications

Published:2014-07 Issue: Volume: Page:
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Container-title:2014 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH)
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Author:

Payvand Melika,Rofeh Justin,Sodhi Avantika,Theogarajan Luke

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/6872767/6880472/06880486.pdf?arnumber=6880486

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Text classification in memristor-based spiking neural networks;Neuromorphic Computing and Engineering;2023-01-31

2. A CMOS–memristor hybrid system for implementing stochastic binary spike timing-dependent plasticity;Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences;2022-06-06

3. Memristive devices based hardware for unlabeled data processing;Neuromorphic Computing and Engineering;2022-06-01

4. A Hybrid Memristor/CMOS SNN for Implementing One-Shot Winner-Takes-All Training;2022 IEEE International Symposium on Circuits and Systems (ISCAS);2022-05-28

5. Device-aware Circuit Design for Robust Memristive Neuromorphic Systems with STDP-based Learning;ACM Journal on Emerging Technologies in Computing Systems;2020-07-14

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