{"title":"非线性前馈跟踪仪表自适应信号处理算法的综合","authors":"V. M. Artyushenko, V. I. Volovach","doi":"10.1109/DYNAMICS.2018.8601431","DOIUrl":null,"url":null,"abstract":"We considered the issues of synthesis of the algorithms for adaptive nonlinear signal processing using feed-forward blocks of nonlinear transformation under the influence of non-Gaussian noise with unknown density of distribution of instantaneous values or its envelope. It is shown that to plot the adaptive feed-forward blocks of nonlinear transformation, the algorithms for estimating the parameters of linear model of probability density function of noise can be used. This model is presented in the form of a generalized polynomial of decomposition in a series of linearly independent functions, and, also, in the form of nonlinear models, such as generalized Gaussian distribution and abnormally cluttered distribution.","PeriodicalId":394567,"journal":{"name":"2018 Dynamics of Systems, Mechanisms and Machines (Dynamics)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Synthesis of Algorithms of Adaptive Signal Processing for Tracking Meters Using Nonlinear Blocks with Feed-Forward\",\"authors\":\"V. M. Artyushenko, V. I. Volovach\",\"doi\":\"10.1109/DYNAMICS.2018.8601431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We considered the issues of synthesis of the algorithms for adaptive nonlinear signal processing using feed-forward blocks of nonlinear transformation under the influence of non-Gaussian noise with unknown density of distribution of instantaneous values or its envelope. It is shown that to plot the adaptive feed-forward blocks of nonlinear transformation, the algorithms for estimating the parameters of linear model of probability density function of noise can be used. This model is presented in the form of a generalized polynomial of decomposition in a series of linearly independent functions, and, also, in the form of nonlinear models, such as generalized Gaussian distribution and abnormally cluttered distribution.\",\"PeriodicalId\":394567,\"journal\":{\"name\":\"2018 Dynamics of Systems, Mechanisms and Machines (Dynamics)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Dynamics of Systems, Mechanisms and Machines (Dynamics)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DYNAMICS.2018.8601431\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Dynamics of Systems, Mechanisms and Machines (Dynamics)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DYNAMICS.2018.8601431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Synthesis of Algorithms of Adaptive Signal Processing for Tracking Meters Using Nonlinear Blocks with Feed-Forward
We considered the issues of synthesis of the algorithms for adaptive nonlinear signal processing using feed-forward blocks of nonlinear transformation under the influence of non-Gaussian noise with unknown density of distribution of instantaneous values or its envelope. It is shown that to plot the adaptive feed-forward blocks of nonlinear transformation, the algorithms for estimating the parameters of linear model of probability density function of noise can be used. This model is presented in the form of a generalized polynomial of decomposition in a series of linearly independent functions, and, also, in the form of nonlinear models, such as generalized Gaussian distribution and abnormally cluttered distribution.