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Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/22696Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dong, Z | - |
| dc.contributor.author | Lai, CS | - |
| dc.contributor.author | Zhang, Z | - |
| dc.contributor.author | Qi, D | - |
| dc.contributor.author | Gao, M | - |
| dc.contributor.author | Duan, S | - |
| dc.date.accessioned | 2021-05-17T06:39:35Z | - |
| dc.date.available | 2021-05-17T06:39:35Z | - |
| dc.date.issued | 2021-04-22 | - |
| dc.identifier.citation | Dong, Z., Lai, C.S., Zhang, Z., Qi, D., Gao, M., Duan, S. (2021) 'Neuromorphic Extreme Learning Machines with Bimodal Memristive Synapses', Neurocomputing, 453, pp. 38-49. doi: 10.1016/j.neucom.2021.04.049. | en_US |
| dc.identifier.issn | 0925-2312 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/22696 | - |
| dc.description | © 2021 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.neucom.2021.04.049 | en_US |
| dc.description.sponsorship | National Natural Science Foundation of China; Fundamental Research Funds for the Provincial Universities of Zhejiang; Brunel Research Initiative and Enterprise Fund. | en_US |
| dc.format.extent | 38 - 49 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | bimodal behavior | en_US |
| dc.subject | extreme learning machine | en_US |
| dc.subject | image super-resolution | en_US |
| dc.subject | Neuromorphic hardware implementation | en_US |
| dc.title | Neuromorphic Extreme Learning Machines with Bimodal Memristive Synapses | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1016/j.neucom.2021.04.049 | - |
| dc.relation.isPartOf | Neurocomputing | - |
| pubs.publication-status | Published | - |
| pubs.volume | 453 | - |
| dc.identifier.eissn | 1872-8286 | - |
| Appears in Collections: | Dept of Electronic and Electrical Engineering Embargoed Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Embargoed until 22 Apr 2022 | 6.42 MB | Adobe PDF | View/Open |
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