{"title":"基于Lyapunov稳定性理论的二维自适应非线性滤波器","authors":"S. Sakrani, M. Sayadi, F. Fnaiech","doi":"10.1109/ISPA.2003.1296470","DOIUrl":null,"url":null,"abstract":"In this paper, a new 2D adaptive nonlinear filter is proposed. Its stability is guaranteed using Lyapunov stability theory. This algorithm profits of the matrix structure of the window (mask), used to define the 2D signal as a nonlinear model of exponential form. This nonlinear exponential model may be easily expanded in a Taylor series leading a higher order polynomial filter. Using the Lyapunov stability theory, it is shown that the new algorithm is independent of the stochastic character of the input signal. Simulation results highlight the efficiency of the new algorithm.","PeriodicalId":218932,"journal":{"name":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A new 2D adaptive nonlinear filter based on the Lyapunov stability theory\",\"authors\":\"S. Sakrani, M. Sayadi, F. Fnaiech\",\"doi\":\"10.1109/ISPA.2003.1296470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new 2D adaptive nonlinear filter is proposed. Its stability is guaranteed using Lyapunov stability theory. This algorithm profits of the matrix structure of the window (mask), used to define the 2D signal as a nonlinear model of exponential form. This nonlinear exponential model may be easily expanded in a Taylor series leading a higher order polynomial filter. Using the Lyapunov stability theory, it is shown that the new algorithm is independent of the stochastic character of the input signal. Simulation results highlight the efficiency of the new algorithm.\",\"PeriodicalId\":218932,\"journal\":{\"name\":\"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2003.1296470\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2003.1296470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new 2D adaptive nonlinear filter based on the Lyapunov stability theory
In this paper, a new 2D adaptive nonlinear filter is proposed. Its stability is guaranteed using Lyapunov stability theory. This algorithm profits of the matrix structure of the window (mask), used to define the 2D signal as a nonlinear model of exponential form. This nonlinear exponential model may be easily expanded in a Taylor series leading a higher order polynomial filter. Using the Lyapunov stability theory, it is shown that the new algorithm is independent of the stochastic character of the input signal. Simulation results highlight the efficiency of the new algorithm.