{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T21:54:31Z","timestamp":1740174871843,"version":"3.37.3"},"reference-count":23,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,8,26]],"date-time":"2021-08-26T00:00:00Z","timestamp":1629936000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61971438","2020JM-345","2020JQ-482"],"award-info":[{"award-number":["61971438","2020JM-345","2020JQ-482"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007128","name":"Natural Science Foundation of Shaanxi Province","doi-asserted-by":"publisher","award":["61971438","2020JM-345","2020JQ-482"],"award-info":[{"award-number":["61971438","2020JM-345","2020JQ-482"]}],"id":[{"id":"10.13039\/501100007128","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mobile Information Systems"],"published-print":{"date-parts":[[2021,8,26]]},"abstract":"<jats:p>Concerned with the problems that the extracted features are the absence of objectivity for radar emitter signal intrapulse data because of relying on priori knowledge, a novel method is proposed. First, this method gets the sparse autoencoder by adding certain restrain to the autoencoder. Second, by optimizing the sparse autoencoder and confirming the training scheme, intrapulse deep features are autoextracted with encoder layer parameters. The method extracts the eigenvectors of six typical radar emitter signals and uses them as inputs to a support vector machine classifier. The experimental results show that the method has higher accuracy in the case of large signal-to-noise ratio. The simulation verifies that the extracted features are feasible.<\/jats:p>","DOI":"10.1155\/2021\/6870938","type":"journal-article","created":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T19:50:10Z","timestamp":1630093810000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["Deep Feature Autoextraction Method for Intrapulse Data of Radar Emitter Signal"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-7791-7197","authenticated-orcid":true,"given":"Shiqiang","family":"Wang","sequence":"first","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-4847-5748","authenticated-orcid":true,"given":"Caiyun","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Basic Science, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-4177-0434","authenticated-orcid":true,"given":"Chang","family":"Luo","sequence":"additional","affiliation":[{"name":"Troops of 78092, Chengdu 610000, China"},{"name":"National Defence University, Joint Operations College, Beijing 100080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-0450-8103","authenticated-orcid":true,"given":"Huiyong","family":"Zeng","sequence":"additional","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0461-6107","authenticated-orcid":true,"given":"Guimei","family":"Zheng","sequence":"additional","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-8580-5099","authenticated-orcid":true,"given":"Qin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-7737-7576","authenticated-orcid":true,"given":"Juan","family":"Bai","sequence":"additional","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-4041-5388","authenticated-orcid":true,"given":"Binfeng","family":"Zong","sequence":"additional","affiliation":[{"name":"Air and Missile Defense College, Air Force Engineering University, Xi\u2019an 710051, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/taes.2017.2667142"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/tcsii.2018.2819666"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1049\/iet-rsn.2019.0040"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2892526"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/icassp.2018.8462139"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-017-2711-7"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2907159"},{"first-page":"1","article-title":"Clustering and unsupervised anomaly detection with l2 normalized deep auto-encoder representations","author":"C. Aytekin","key":"8"},{"volume-title":"Hamiltonian Variational Auto-Encoder","year":"2018","author":"A. L. Caterini","key":"9"},{"first-page":"2967","article-title":"Auto-encoder by forest","author":"J. Feng","key":"10"},{"key":"11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.knosys.2017.10.024","article-title":"Intelligent fault diagnosis of rolling bearing using deep wavelet auto-encoder with extreme learning machine","volume":"140","author":"H. Shao","year":"2018","journal-title":"Knowl.-Based Syst."},{"first-page":"206","article-title":"Foldingnet: point cloud auto-encoder via deep grid deformation","author":"Y. Yang","key":"12"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"14","first-page":"899","article-title":"Generalized denoising auto-encoders as generative models","volume":"1","author":"Y. Bengio","year":"2013","journal-title":"News in Physiological Sciences"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1109\/ijcnn.2015.7280568"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1109\/ccdc.2015.7162335"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1109\/wcica.2014.7052920"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1109\/igarss.2014.6947062"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1007\/s12555-016-0160-1"},{"first-page":"4602","article-title":"Feature selection using multiple auto-encoders","author":"X. Guo","key":"20"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1039\/c7mb00188f"},{"issue":"9","key":"22","first-page":"2774","article-title":"Sparse denoising autoencoder application in identification of counterfeit pharmaceutical","volume":"36","author":"H. H. Yang","year":"2016","journal-title":"Spectroscopy and Spectral Analysis"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1109\/icmlc.2018.8526953"}],"container-title":["Mobile Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/downloads.hindawi.com\/journals\/misy\/2021\/6870938.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/downloads.hindawi.com\/journals\/misy\/2021\/6870938.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/downloads.hindawi.com\/journals\/misy\/2021\/6870938.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T19:50:14Z","timestamp":1630093814000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.hindawi.com\/journals\/misy\/2021\/6870938\/"}},"subtitle":[],"editor":[{"given":"Sang-Bing","family":"Tsai","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,8,26]]},"references-count":23,"alternative-id":["6870938","6870938"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1155\/2021\/6870938","relation":{},"ISSN":["1875-905X","1574-017X"],"issn-type":[{"type":"electronic","value":"1875-905X"},{"type":"print","value":"1574-017X"}],"subject":[],"published":{"date-parts":[[2021,8,26]]}}}