QQ客服 官方微博 反馈留言

浏览/检索结果: 共5条，第1-5条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Long short-term memory networks in memristor crossbar arrays 期刊论文 Nature Machine Intelligence, 2019, 卷号: Vol.1, 页码: 49-57 作者:  Can Li;  Zhongrui Wang;  Mingyi Rao;  Daniel Belkin;  Wenhao Song 收藏  |  浏览/下载：9/0  |  提交时间：2019/12/13 Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network 期刊论文 JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY, 2019, 卷号: 35, 期号: 1, 页码: 168-175 作者:  Hu, Qiangfei;  Liu, Yuchen;  Zhang, Tao;  Geng, Shujiang;  Wang, Fuhui 收藏  |  浏览/下载：1/0  |  提交时间：2021/02/02 Ni-Cr-Mo-V steel  Deep sea corrosion  Design of experiment  Artificial neural network   Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network 期刊论文 JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY, 2019, 卷号: 35, 期号: 1, 页码: 168-175 作者:  Hu, Qiangfei;  Liu, Yuchen;  Zhang, Tao;  Geng, Shujiang;  Wang, Fuhui 收藏  |  浏览/下载：2/0  |  提交时间：2021/02/02 Ni-Cr-Mo-V steel  Deep sea corrosion  Design of experiment  Artificial neural network   Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network 期刊论文 JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY, 2019, 卷号: 35, 期号: 1, 页码: 168-175 作者:  Hu, Qiangfei;  Liu, Yuchen;  Zhang, Tao;  Geng, Shujiang;  Wang, Fuhui 收藏  |  浏览/下载：1/0  |  提交时间：2021/02/02 Ni-Cr-Mo-V steel  Deep sea corrosion  Design of experiment  Artificial neural network   Fully memristive neural networks for pattern classification with unsupervised learning 期刊论文 Nature Electronics, 2018, 卷号: Vol.1 No.2, 页码: 137-145 作者:  Zhongrui Wang;  Saumil Joshi;  Sergey Savel’ev;  Wenhao Song;  Rivu Midya 收藏  |  浏览/下载：11/0  |  提交时间：2019/12/26 Computational  science  Electrical  and  electronic  engineering  Materials  for  devices  Nanoscale  devices