{"title":"Adaptive filtering for non-Gaussian processes","authors":"P. Kidmose","doi":"10.1109/ICASSP.2000.861999","DOIUrl":null,"url":null,"abstract":"A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double-talk in the acoustical echo-cancellation problem.","PeriodicalId":164817,"journal":{"name":"2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2000.861999","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double-talk in the acoustical echo-cancellation problem.