Extraction of gravitational wave signals with optimized convolutional neural network
文献类型：期刊论文
| 作者 | Luo, Hua-Mei; Lin, Wenbin3,4; Chen, Zu-Cheng; Huang, Qing-Guo
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| 刊名 | FRONTIERS OF PHYSICS
 |
| 出版日期 | 2020 |
| 卷号 | 15期号:1页码:14601 |
| ISSN号 | 2095-0462 |
| DOI | 10.1007/s11467-019-0936-x |
| 英文摘要 | Gabbard et al. have demonstrated that convolutional neural networks can achieve the sensitivity of matched filtering in the recognization of the gravitational-wave signals with high efficiency [Phys. Rev. Lett. 120, 141103 (2018)]. In this work we show that their model can be optimized for better accuracy. The convolutional neural networks typically have alternating convolutional layers and max pooling layers, followed by a small number of fully connected layers. We increase the stride in the max pooling layer by 1, followed by a dropout layer to alleviate overfitting in the original model. We find that these optimizations can effectively increase the area under the receiver operating characteristic curve for various tests on the same dataset. |
| 学科主题 | Physics |
| 语种 | 英语 |
| 源URL | [http://ir.itp.ac.cn/handle/311006/26981]  |
| 专题 | 理论物理研究所_理论物理所1978-2010年知识产出 |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Phys Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China 3.Southwest Jiaotong Univ, Sch Math, Chengdu 610031, Sichuan, Peoples R China 4.Southwest Jiaotong Univ, Sch Phys Sci & Technol, Chengdu 610031, Sichuan, Peoples R China 5.Univ South China, Sch Math & Phys, Hengyang 421001, Peoples R China |
| 推荐引用方式 GB/T 7714 | Luo, Hua-Mei,Lin, Wenbin,Chen, Zu-Cheng,et al. Extraction of gravitational wave signals with optimized convolutional neural network[J]. FRONTIERS OF PHYSICS,2020,15(1):14601. |
| APA | Luo, Hua-Mei,Lin, Wenbin,Chen, Zu-Cheng,&Huang, Qing-Guo.(2020).Extraction of gravitational wave signals with optimized convolutional neural network.FRONTIERS OF PHYSICS,15(1),14601. |
| MLA | Luo, Hua-Mei,et al."Extraction of gravitational wave signals with optimized convolutional neural network".FRONTIERS OF PHYSICS 15.1(2020):14601. |
入库方式： OAI收割
来源：理论物理研究所
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