{"title":"Fast Computing of Non-uniform Sampling Positions for Real Signals","authors":"P. Kovács, Viktor Vad","doi":"10.1109/SYNASC.2013.27","DOIUrl":null,"url":null,"abstract":"There is a wide range of applications of non-equidistant discretization of real signals. For instance, in computer graphics, Fourier analysis, identification and control theories, etc. They have the common ability to describe dynamical systems as well. In this paper we provide a fast algorithm based on an existing mathematical model to compute a non-uniform grid for representing different types of signals. In order to do that we need new concepts for constructing an effective numerical solution. Additionally, two experiments are performed to investigate the accuracy of the method. Finally, we also present a parallel implementation in CUDA which can further improve the execution time.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2013.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
There is a wide range of applications of non-equidistant discretization of real signals. For instance, in computer graphics, Fourier analysis, identification and control theories, etc. They have the common ability to describe dynamical systems as well. In this paper we provide a fast algorithm based on an existing mathematical model to compute a non-uniform grid for representing different types of signals. In order to do that we need new concepts for constructing an effective numerical solution. Additionally, two experiments are performed to investigate the accuracy of the method. Finally, we also present a parallel implementation in CUDA which can further improve the execution time.