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Attention-Enhanced Domain Adversarial Training for Robust Automatic Modulation Classification of Radar Signals.

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Title: Attention-Enhanced Domain Adversarial Training for Robust Automatic Modulation Classification of Radar Signals.
Authors: Kou, Liang1, 578185066@qq.com, Wang, Guoyu2, cemee_hanhui@163.com, Han, Hui3, xuxiong2008@foxmail.com, Xu, Xiong4, kouliang@hrbeu.edu.cn
Source: International Journal of Computers, Communications & Control; Jun2026, Vol. 21 Issue 3, p1-11, 11p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 195141079
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Attention-Enhanced Domain Adversarial Training for Robust Automatic Modulation Classification of Radar Signals.
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  Data: <searchLink fieldCode="AU" term="%22Kou%2C+Liang%22">Kou, Liang</searchLink><relatesTo>1</relatesTo>, <i>578185066@qq.com</i><br /><searchLink fieldCode="AU" term="%22Wang%2C+Guoyu%22">Wang, Guoyu</searchLink><relatesTo>2</relatesTo>, <i>cemee_hanhui@163.com</i><br /><searchLink fieldCode="AU" term="%22Han%2C+Hui%22">Han, Hui</searchLink><relatesTo>3</relatesTo>, <i>xuxiong2008@foxmail.com</i><br /><searchLink fieldCode="AU" term="%22Xu%2C+Xiong%22">Xu, Xiong</searchLink><relatesTo>4</relatesTo>, <i>kouliang@hrbeu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Computers%2C+Communications+%26+Control%22">International Journal of Computers, Communications & Control</searchLink>; Jun2026, Vol. 21 Issue 3, p1-11, 11p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=195141079
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.15837/ijccc.2026.3.7097
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      – Code: eng
        Text: English
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        PageCount: 11
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      – TitleFull: Attention-Enhanced Domain Adversarial Training for Robust Automatic Modulation Classification of Radar Signals.
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            NameFull: Kou, Liang
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            NameFull: Wang, Guoyu
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            NameFull: Han, Hui
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              Text: Jun2026
              Type: published
              Y: 2026
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              Value: 21
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