{"title":"一种窄带有源噪声控制系统的自适应神经控制器","authors":"Minh-Canh Huynh, Cheng-Yuan Chang","doi":"10.1109/NICS54270.2021.9701565","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel adaptive neural network controller which can operate effectively in both linear and nonlinear narrowband active noise control systems. The advantage of the proposed method is a simple structure with three network layers, which its adaptive coefficients are updated online. Algorithm analysis of the proposed method is presented in this paper. The improved performance is verified by computer simulations through comparison with the traditional method.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"1 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel adaptive neural controller for narrowband active noise control systems\",\"authors\":\"Minh-Canh Huynh, Cheng-Yuan Chang\",\"doi\":\"10.1109/NICS54270.2021.9701565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel adaptive neural network controller which can operate effectively in both linear and nonlinear narrowband active noise control systems. The advantage of the proposed method is a simple structure with three network layers, which its adaptive coefficients are updated online. Algorithm analysis of the proposed method is presented in this paper. The improved performance is verified by computer simulations through comparison with the traditional method.\",\"PeriodicalId\":296963,\"journal\":{\"name\":\"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)\",\"volume\":\"1 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NICS54270.2021.9701565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NICS54270.2021.9701565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel adaptive neural controller for narrowband active noise control systems
This paper proposes a novel adaptive neural network controller which can operate effectively in both linear and nonlinear narrowband active noise control systems. The advantage of the proposed method is a simple structure with three network layers, which its adaptive coefficients are updated online. Algorithm analysis of the proposed method is presented in this paper. The improved performance is verified by computer simulations through comparison with the traditional method.
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