{"title":"一种具有进化遗忘因子的RLS算法","authors":"Sheng Zhang, Jiashu Zhang","doi":"10.1109/IWSDA.2015.7458406","DOIUrl":null,"url":null,"abstract":"This paper presents a novel recursive least squares (RLS) algorithm which automatically determines its forgetting factor by an evolutionary method. The evolutionary method increases or decreases the forgetting factor by comparing the output error with a threshold. The experimental results show that the proposed algorithm has fast convergence speed and small steady-state error compared to the RLS.","PeriodicalId":371829,"journal":{"name":"2015 Seventh International Workshop on Signal Design and its Applications in Communications (IWSDA)","volume":"2676 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An RLS algorithm with evolving forgetting factor\",\"authors\":\"Sheng Zhang, Jiashu Zhang\",\"doi\":\"10.1109/IWSDA.2015.7458406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel recursive least squares (RLS) algorithm which automatically determines its forgetting factor by an evolutionary method. The evolutionary method increases or decreases the forgetting factor by comparing the output error with a threshold. The experimental results show that the proposed algorithm has fast convergence speed and small steady-state error compared to the RLS.\",\"PeriodicalId\":371829,\"journal\":{\"name\":\"2015 Seventh International Workshop on Signal Design and its Applications in Communications (IWSDA)\",\"volume\":\"2676 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Seventh International Workshop on Signal Design and its Applications in Communications (IWSDA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWSDA.2015.7458406\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Seventh International Workshop on Signal Design and its Applications in Communications (IWSDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWSDA.2015.7458406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a novel recursive least squares (RLS) algorithm which automatically determines its forgetting factor by an evolutionary method. The evolutionary method increases or decreases the forgetting factor by comparing the output error with a threshold. The experimental results show that the proposed algorithm has fast convergence speed and small steady-state error compared to the RLS.
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