{"title":"具有相干准则的低复杂度核仿射型算法","authors":"F. Albu, K. Nishikawa","doi":"10.1109/ICSIGSYS.2017.7967076","DOIUrl":null,"url":null,"abstract":"In this paper, two new kernel adaptive algorithms are proposed. An approximation is used in order to derive the pseudo kernel affine projection algorithm and the pseudo kernel proportionate affine projection algorithm, respectively. The computational efficiency and performance of the proposed algorithms is verified for a nonlinear system identification application.","PeriodicalId":212068,"journal":{"name":"2017 International Conference on Signals and Systems (ICSigSys)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Low complexity kernel affine projection-type algorithms with a coherence criterion\",\"authors\":\"F. Albu, K. Nishikawa\",\"doi\":\"10.1109/ICSIGSYS.2017.7967076\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, two new kernel adaptive algorithms are proposed. An approximation is used in order to derive the pseudo kernel affine projection algorithm and the pseudo kernel proportionate affine projection algorithm, respectively. The computational efficiency and performance of the proposed algorithms is verified for a nonlinear system identification application.\",\"PeriodicalId\":212068,\"journal\":{\"name\":\"2017 International Conference on Signals and Systems (ICSigSys)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Signals and Systems (ICSigSys)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIGSYS.2017.7967076\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Signals and Systems (ICSigSys)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIGSYS.2017.7967076","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low complexity kernel affine projection-type algorithms with a coherence criterion
In this paper, two new kernel adaptive algorithms are proposed. An approximation is used in order to derive the pseudo kernel affine projection algorithm and the pseudo kernel proportionate affine projection algorithm, respectively. The computational efficiency and performance of the proposed algorithms is verified for a nonlinear system identification application.