{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T05:16:58Z","timestamp":1737004618869,"version":"3.33.0"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T00:00:00Z","timestamp":1729728000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T00:00:00Z","timestamp":1729728000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62101587"],"award-info":[{"award-number":["62101587"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,24]]},"DOI":"10.1109\/wcsp62071.2024.10826867","type":"proceedings-article","created":{"date-parts":[[2025,1,14]],"date-time":"2025-01-14T19:41:04Z","timestamp":1736883664000},"page":"782-788","source":"Crossref","is-referenced-by-count":0,"title":["A Multi-Feature Time-Series Data Generation Method for LEO Electromagnetic Monitoring Systems"],"prefix":"10.1109","author":[{"given":"Yuxuan","family":"Yang","sequence":"first","affiliation":[{"name":"Academy of Military Sciences, People's Liberation Army,Beijing,China"}]},{"given":"Boyu","family":"Deng","sequence":"additional","affiliation":[{"name":"Tsinghua University,Beijing,China"}]},{"given":"Jingchao","family":"Wang","sequence":"additional","affiliation":[{"name":"Academy of Military Sciences, People's Liberation Army,Beijing,China"}]},{"given":"Jizheng","family":"Sun","sequence":"additional","affiliation":[{"name":"Academy of Military Sciences, People's Liberation Army,Beijing,China"}]},{"given":"Tuo","family":"Yang","sequence":"additional","affiliation":[{"name":"Xidian University,Xian,China"}]},{"given":"Xiaoyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Academy of Military Sciences, People's Liberation Army,Beijing,China"}]}],"member":"263","reference":[{"issue":"1","key":"ref1","first-page":"40","article-title":"Deep Generative Models: A Review","volume":"48","author":"Hu","year":"2022","journal-title":"Acta Automatica Sinica"},{"issue":"11","key":"ref2","first-page":"31","article-title":"A Review of SAR Data Augmentation Based on GANs","volume":"42","author":"Huang","year":"2021","journal-title":"Journal of Ordnance Equipment Engineering"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref4","article-title":"Generative adversarial nets","volume":"27","author":"Goodfellow","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1411.1784"},{"key":"ref6","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","volume-title":"Proceedings of the 4th International Conference on Learning Representations","author":"Radford","year":"2016"},{"key":"ref7","first-page":"2642","article-title":"Conditional Image Synthesis with Auxiliary Classifier GANs","volume-title":"Proceedings of the 34th International Conference on Machine Learning","author":"Odena","year":"2017"},{"journal-title":"T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling","year":"2019","author":"Ramponi","key":"ref8"},{"key":"ref9","article-title":"Data Augmentation for Time Series Classification Using Convolutional Neural Networks","volume-title":"ECML\/PKDD Workshop on AALTD","author":"Guennec","year":"2016"},{"journal-title":"Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs","year":"2017","author":"Esteban","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2018.00916"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2018.00745"},{"key":"ref14","first-page":"214","article-title":"Wasserstein Generative Adversarial Networks","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Arjovsky","year":"2017"},{"key":"ref15","article-title":"Improved training of Wasserstein GANs","volume":"30","author":"Gulrajani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"journal-title":"TTS-CGAN: A Transformer Time-Series Conditional GAN for Biosignal Data Augmentation","year":"2022","author":"Li","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3623086"}],"event":{"name":"2024 16th International Conference on Wireless Communications and Signal Processing (WCSP)","start":{"date-parts":[[2024,10,24]]},"location":"Hefei, China","end":{"date-parts":[[2024,10,26]]}},"container-title":["2024 16th International Conference on Wireless Communications and Signal Processing (WCSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10826574\/10826586\/10826867.pdf?arnumber=10826867","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T07:01:07Z","timestamp":1736924467000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10826867\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,24]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/wcsp62071.2024.10826867","relation":{},"subject":[],"published":{"date-parts":[[2024,10,24]]}}}