{"title":"Identification of Hammerstein model using cubic splines and FIR filtering","authors":"M. Gasparini, L. Romoli, S. Cecchi, F. Piazza","doi":"10.1109/ISPA.2013.6703766","DOIUrl":null,"url":null,"abstract":"Nonlinear models are exploited in the field of digital audio systems for modelling most of real-world devices that show a nonlinear behaviour. Among nonlinear models, Hammerstein systems are realized through a static nonlinearity cascaded with a linear filter. In this paper, the Hammerstein coefficients are estimated using an adaptive Catmull-Rom cubic spline for the static nonlinearity and an adaptive FIR filter for the dynamic linear system also introducing a preprocessing for the time delay estimation. Experimental results confirm the effectiveness of the proposed approach, making also comparisons with existing techniques of the state of the art.","PeriodicalId":425029,"journal":{"name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2013.6703766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Nonlinear models are exploited in the field of digital audio systems for modelling most of real-world devices that show a nonlinear behaviour. Among nonlinear models, Hammerstein systems are realized through a static nonlinearity cascaded with a linear filter. In this paper, the Hammerstein coefficients are estimated using an adaptive Catmull-Rom cubic spline for the static nonlinearity and an adaptive FIR filter for the dynamic linear system also introducing a preprocessing for the time delay estimation. Experimental results confirm the effectiveness of the proposed approach, making also comparisons with existing techniques of the state of the art.