{"title":"进一步讨论了自适应滤波器对小波收缩方法的改进","authors":"Teng-Chieh Yang, Y. Chiang, F. Chang","doi":"10.1109/ICSSE.2016.7551646","DOIUrl":null,"url":null,"abstract":"We earlier proposed a novel on-line denoising structure which utilized the adaptive filter to improve the wavelet shrinkage and did acquire some positive results. In this paper, we will have a further discussion based on this structure. Topics include parameter adjustments, LMS non-causal cases, the decision of both DWT level and mother wavelet, and RLS algorithm. Based on these discussions, we will be able to fine tune our denoising structure and come up with better results.","PeriodicalId":175283,"journal":{"name":"2016 International Conference on System Science and Engineering (ICSSE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Further discussions on adaptive filters to improve the wavelet shrinkage method\",\"authors\":\"Teng-Chieh Yang, Y. Chiang, F. Chang\",\"doi\":\"10.1109/ICSSE.2016.7551646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We earlier proposed a novel on-line denoising structure which utilized the adaptive filter to improve the wavelet shrinkage and did acquire some positive results. In this paper, we will have a further discussion based on this structure. Topics include parameter adjustments, LMS non-causal cases, the decision of both DWT level and mother wavelet, and RLS algorithm. Based on these discussions, we will be able to fine tune our denoising structure and come up with better results.\",\"PeriodicalId\":175283,\"journal\":{\"name\":\"2016 International Conference on System Science and Engineering (ICSSE)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on System Science and Engineering (ICSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSE.2016.7551646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2016.7551646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Further discussions on adaptive filters to improve the wavelet shrinkage method
We earlier proposed a novel on-line denoising structure which utilized the adaptive filter to improve the wavelet shrinkage and did acquire some positive results. In this paper, we will have a further discussion based on this structure. Topics include parameter adjustments, LMS non-causal cases, the decision of both DWT level and mother wavelet, and RLS algorithm. Based on these discussions, we will be able to fine tune our denoising structure and come up with better results.