{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,30]],"date-time":"2026-05-30T05:02:12Z","timestamp":1780117332301,"version":"3.54.0"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["QTZX25070"],"award-info":[{"award-number":["QTZX25070"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["ZYTS25205"],"award-info":[{"award-number":["ZYTS25205"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017596","name":"Natural Science Basic Research Program of Shaanxi Province","doi-asserted-by":"publisher","award":["2025JC-YBQN-795"],"award-info":[{"award-number":["2025JC-YBQN-795"]}],"id":[{"id":"10.13039\/501100017596","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2025M771550"],"award-info":[{"award-number":["2025M771550"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2025T180431"],"award-info":[{"award-number":["2025T180431"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shaanxi Province Innovation Capability Support Plan","award":["2023-CX-TD-09"],"award-info":[{"award-number":["2023-CX-TD-09"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276197"],"award-info":[{"award-number":["62276197"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62506285"],"award-info":[{"award-number":["62506285"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cogn. Commun. Netw."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/tccn.2026.3695841","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T19:37:05Z","timestamp":1779478625000},"page":"8492-8505","source":"Crossref","is-referenced-by-count":0,"title":["MSN: Rethinking Cross-Domain Automatic Modulation Recognition via Decoupled Modulation Signal Normalization"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-9373-5361","authenticated-orcid":false,"given":"Yifan","family":"Chen","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0379-2042","authenticated-orcid":false,"given":"Xiangrong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9606-7052","authenticated-orcid":false,"given":"Guanchun","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4132-149X","authenticated-orcid":false,"given":"Ziyi","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3354-9617","authenticated-orcid":false,"given":"Licheng","family":"Jiao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i15.29606"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2021.3076234"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447734"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2015.2440189"},{"issue":"9","key":"ref5","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.cja.2021.08.016","article-title":"Large-scale real-world radio signal recognition with deep learning","volume":"35","author":"Ya","year":"2022","journal-title":"Chin. J. Aeronaut."},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2019.2949308"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2025.3615307"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-44188-7_16"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2018.2835460"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2021.3102656"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2020.2999453"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3191783"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/VTC2020-Spring48590.2020.9128408"},{"key":"ref14","first-page":"2488","article-title":"How does batch normalization help optimization?","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Santurkar"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref16","article-title":"Layer normalization","author":"Lei Ba","year":"2016","journal-title":"arXiv:1607.06450"},{"key":"ref17","article-title":"Instance normalization: The missing ingredient for fast stylization","author":"Ulyanov","year":"2016","journal-title":"arXiv:1607.08022"},{"key":"ref18","first-page":"12360","article-title":"Root mean square layer normalization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref19","article-title":"Reversible instance normalization for accurate time-series forecasting against distribution shift","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kim"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2010.2076347"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/26.823550"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM.1999.822675"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM.2000.904013"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1049\/iet-com:20050176"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8121407"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1049\/ip-com:19960752"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/VETECS.2004.1388960"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1515\/bpasts-2016-0028"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1155\/int\/4067323"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2024.3453559"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/electronics13173408"},{"key":"ref32","first-page":"18387","article-title":"Batch normalization provably avoids ranks collapse for randomly initialised deep networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Daneshmand"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25914"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467330"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/26.747819"},{"key":"ref36","first-page":"3360","article-title":"Exponential expressivity in deep neural networks through transient chaos","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"29","author":"Poole"},{"key":"ref37","article-title":"Deep information propagation","volume-title":"Proc. Int. Conf. Learn. Representations (ICLR)","author":"Schoenholz"},{"key":"ref38","first-page":"342","article-title":"Kernel methods for deep learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"22","author":"Cho"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2024.3410291"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5862"},{"key":"ref41","first-page":"8068","article-title":"Batch-instance normalization for adaptively style-invariant neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Nam"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s13389-012-0038-y"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00343"},{"issue":"1","key":"ref44","first-page":"1","article-title":"Radio machine learning dataset generation with GNU radio","volume-title":"Proc. GNU Radio Conf.","volume":"1","author":"O\u2019Shea"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2018.2797022"},{"key":"ref46","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2022.103650","article-title":"Deep learning based automatic modulation recognition: Models, datasets, and challenges","volume":"129","author":"Zhang","year":"2022","journal-title":"Digit. Signal Process."},{"key":"ref47","first-page":"8026","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Paszke"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_1"},{"issue":"86","key":"ref49","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Cognitive Communications and Networking"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6687307\/11304002\/11534300.pdf?arnumber=11534300","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,30]],"date-time":"2026-05-30T04:22:44Z","timestamp":1780114964000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11534300\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/tccn.2026.3695841","relation":{},"ISSN":["2332-7731","2372-2045"],"issn-type":[{"value":"2332-7731","type":"electronic"},{"value":"2372-2045","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}