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DOI | 10.1038/s41467-019-12343-x |
Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits | |
Bayat, F. Merrikh1; Prezioso, M.1; Chakrabarti, B.1; Nili, H.1; Kataeva, I.2; Strukov, D.1 | |
2019-09-20 | |
发表期刊 | NATURE COMMUNICATIONS
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ISSN | 2041-1723 |
出版年 | 2018 |
卷号 | 9 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Japan |
英文摘要 | The progress in the field of neural computation hinges on the use of hardware more efficient than the conventional microprocessors. Recent works have shown that mixed-signal integrated memristive circuits, especially their passive (OT1R) variety, may increase the neuromorphic network performance dramatically, leaving far behind their digital counterparts. The major obstacle, however, is immature memristor technology so that only limited functionality has been reported. Here we demonstrate operation of one-hidden layer perceptron classifier entirely in the mixed-signal integrated hardware, comprised of two passive 20 x 20 metal-oxide memristive crossbar arrays, board-integrated with discrete conventional components. The demonstrated network, whose hardware complexity is almost 10x higher as compared to previously reported functional classifier circuits based on passive memristive crossbars, achieves classification fidelity within 3% of that obtained in simulations, when using ex-situ training. The successful demonstration was facilitated by improvements in fabrication technology of memristors, specifically by lowering variations in their I-V characteristics. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000435082400008 |
WOS关键词 | NEURAL-NETWORKS ; SYNAPSES ; ANALOG ; CLASSIFICATION ; RECOGNITION ; DEVICE ; MEMORY |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/204555 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Calif Santa Barbara, Elect & Comp Engn Dept, Santa Barbara, CA 93117 USA; 2.DENSO CORP, 500-1 Minamiyama,Komenoki Cho, Nisshin 4700111, Japan |
推荐引用方式 GB/T 7714 | Bayat, F. Merrikh,Prezioso, M.,Chakrabarti, B.,et al. Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits[J]. NATURE COMMUNICATIONS,2019,9. |
APA | Bayat, F. Merrikh,Prezioso, M.,Chakrabarti, B.,Nili, H.,Kataeva, I.,&Strukov, D..(2019).Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits.NATURE COMMUNICATIONS,9. |
MLA | Bayat, F. Merrikh,et al."Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits".NATURE COMMUNICATIONS 9(2019). |
条目包含的文件 | 条目无相关文件。 |
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