{"title":"单变量积分算子核的三对角核增强多方差积表示","authors":"A. Okan, M. Demiralp","doi":"10.1109/MCSI.2014.26","DOIUrl":null,"url":null,"abstract":"This work is an extension of very recently developed decomposition method for matrices. That method has been called \"Tridiagonal Matrix Enhanced Multivariance Product Representation, or briefly, TMEMPR. Here, in this work our ultimate goal has been taken as the decomposition of a univariate linear integral operator. Instead of this task we focus on a bivariate function since the kernel of such an operator is a bivariate function. After having a well developed theory it is just a matter of simple translation what we are going to obtain into linear integral operator's decomposition. The main skeleton of the issue has been constructed in this presentation.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Tridiagonal Kernel Enhanced Multivariance Products Representation (TKEMPR) for Univariate Integral Operator Kernels\",\"authors\":\"A. Okan, M. Demiralp\",\"doi\":\"10.1109/MCSI.2014.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work is an extension of very recently developed decomposition method for matrices. That method has been called \\\"Tridiagonal Matrix Enhanced Multivariance Product Representation, or briefly, TMEMPR. Here, in this work our ultimate goal has been taken as the decomposition of a univariate linear integral operator. Instead of this task we focus on a bivariate function since the kernel of such an operator is a bivariate function. After having a well developed theory it is just a matter of simple translation what we are going to obtain into linear integral operator's decomposition. The main skeleton of the issue has been constructed in this presentation.\",\"PeriodicalId\":202841,\"journal\":{\"name\":\"2014 International Conference on Mathematics and Computers in Sciences and in Industry\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Mathematics and Computers in Sciences and in Industry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCSI.2014.26\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSI.2014.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tridiagonal Kernel Enhanced Multivariance Products Representation (TKEMPR) for Univariate Integral Operator Kernels
This work is an extension of very recently developed decomposition method for matrices. That method has been called "Tridiagonal Matrix Enhanced Multivariance Product Representation, or briefly, TMEMPR. Here, in this work our ultimate goal has been taken as the decomposition of a univariate linear integral operator. Instead of this task we focus on a bivariate function since the kernel of such an operator is a bivariate function. After having a well developed theory it is just a matter of simple translation what we are going to obtain into linear integral operator's decomposition. The main skeleton of the issue has been constructed in this presentation.