{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T22:03:09Z","timestamp":1767909789947,"version":"3.49.0"},"reference-count":43,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shenyang Science and Technology Program","award":["23-503-6-16"],"award-info":[{"award-number":["23-503-6-16"]}]},{"name":"Shenyang Science and Technology Program","award":["LJKMZ20220612"],"award-info":[{"award-number":["LJKMZ20220612"]}]},{"name":"Shenyang Science and Technology Program","award":["2022020128-JH6\/1001"],"award-info":[{"award-number":["2022020128-JH6\/1001"]}]},{"name":"Shenyang Science and Technology Program","award":["61971291"],"award-info":[{"award-number":["61971291"]}]},{"name":"Education Department of Liaoning Province","award":["23-503-6-16"],"award-info":[{"award-number":["23-503-6-16"]}]},{"name":"Education Department of Liaoning Province","award":["LJKMZ20220612"],"award-info":[{"award-number":["LJKMZ20220612"]}]},{"name":"Education Department of Liaoning Province","award":["2022020128-JH6\/1001"],"award-info":[{"award-number":["2022020128-JH6\/1001"]}]},{"name":"Education Department of Liaoning Province","award":["61971291"],"award-info":[{"award-number":["61971291"]}]},{"name":"Central Government Leads Local Science and Technology Development Projects","award":["23-503-6-16"],"award-info":[{"award-number":["23-503-6-16"]}]},{"name":"Central Government Leads Local Science and Technology Development Projects","award":["LJKMZ20220612"],"award-info":[{"award-number":["LJKMZ20220612"]}]},{"name":"Central Government Leads Local Science and Technology Development Projects","award":["2022020128-JH6\/1001"],"award-info":[{"award-number":["2022020128-JH6\/1001"]}]},{"name":"Central Government Leads Local Science and Technology Development Projects","award":["61971291"],"award-info":[{"award-number":["61971291"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["23-503-6-16"],"award-info":[{"award-number":["23-503-6-16"]}],"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":["LJKMZ20220612"],"award-info":[{"award-number":["LJKMZ20220612"]}],"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":["2022020128-JH6\/1001"],"award-info":[{"award-number":["2022020128-JH6\/1001"]}],"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":["61971291"],"award-info":[{"award-number":["61971291"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>In response to the problem where neural network models fail to fully learn signal sample features due to an insufficient number of signal samples, leading to a decrease in the model\u2019s ability to recognize signal modulation methods, a few-shot signal modulation mode recognition method based on reinforcement metric meta-learning (RMML) is proposed. This approach, grounded in meta-learning techniques, employs transfer learning to building a feature extraction network that effectively extracts the data features under few-shot conditions. Building on this, by integrating the measurement of features of similar samples and the differences between features of different classes of samples, the metric network\u2019s target loss function is optimized, thereby improving the network\u2019s ability to distinguish between features of different modulation methods. The experimental results demonstrate that this method exhibits a good performance in processing new class signals that have not been previously trained. Under the condition of 5-way 5-shot, when the signal-to-noise ratio (SNR) is 0 dB, this method can achieve an average recognition accuracy of 91.8%, which is 2.8% higher than that of the best-performing baseline method, whereas when the SNR is 18 dB, the model\u2019s average recognition accuracy significantly improves to 98.5%.<\/jats:p>","DOI":"10.3390\/computers14090346","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T15:57:47Z","timestamp":1755878267000},"page":"346","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Method for Few-Shot Modulation Recognition Based on Reinforcement Metric Meta-Learning"],"prefix":"10.3390","volume":"14","author":[{"given":"Fan","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University (SYLU), No. 6 Nanping East Road, Shenyang 110159, China"}]},{"given":"Xiao","family":"Han","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University (SYLU), No. 6 Nanping East Road, Shenyang 110159, China"}]},{"given":"Jinyang","family":"Ren","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University (SYLU), No. 6 Nanping East Road, Shenyang 110159, China"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Electromagnetic Space Security, Xidian University, No. 2 South Taibai Road, Jiaxing 314000, China"}]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang Ligong University (SYLU), No. 6 Nanping East Road, Shenyang 110159, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0990-5581","authenticated-orcid":false,"given":"Peiying","family":"Zhang","sequence":"additional","affiliation":[{"name":"Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum (East China), 66 Changjiang West Road, Qingdao 266580, China"},{"name":"Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Qilu University of Technology (Shandong Academy of Sciences), 3501 Daxue Road, Jinan 250013, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4432-3448","authenticated-orcid":false,"given":"Shaolin","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Technology, Sun Yat-sen University, No. 135 Xingang Xi Road, Guangzhou 510275, China"},{"name":"Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA"},{"name":"Elmore School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1109\/26.664294","article-title":"Algorithms for automatic modulation recognition of communication signals","volume":"46","author":"Nandi","year":"1998","journal-title":"IEEE Trans. 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