{"title":"基于近似度的插值:一种新的插值方法","authors":"Shiyou Lian","doi":"10.36227/TECHRXIV.12552068.V1","DOIUrl":null,"url":null,"abstract":"This paper introduces\nthe measure of approximate-degree and the concept of approximate-degree\nfunction between numerical values, thus developing a new interpolation method\n—— approximation-degree-based interpolation, i.e., AD interpolation.\nOne-dimensional AD interpolation is done directly by using correlative\ninterpolation formulas; n(n>1)-dimensional AD interpolation is\nfirstly separated into n parallel\none-dimensional AD interpolation computations to do respectively, and then got\nresults are synthesized by Sum-Times-Difference formula into a value as the\nresult value of the n-dimensional\ninterpolation. If the parallel processing is used, the efficiency of n-dimensional AD interpolation is almost\nthe same as that of the one-dimensional AD interpolation. Thus it starts a feasible and convenient approach and provides\nan effective method for high-dimensional interpolations. Furthermore,\nif AD interpolation is introduced into machine learning, a new instance-based\nlearning method is expected to be realized.","PeriodicalId":23650,"journal":{"name":"viXra","volume":"47 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Approximation-Degree-Based Interpolation: A New Interpolation Method\",\"authors\":\"Shiyou Lian\",\"doi\":\"10.36227/TECHRXIV.12552068.V1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces\\nthe measure of approximate-degree and the concept of approximate-degree\\nfunction between numerical values, thus developing a new interpolation method\\n—— approximation-degree-based interpolation, i.e., AD interpolation.\\nOne-dimensional AD interpolation is done directly by using correlative\\ninterpolation formulas; n(n>1)-dimensional AD interpolation is\\nfirstly separated into n parallel\\none-dimensional AD interpolation computations to do respectively, and then got\\nresults are synthesized by Sum-Times-Difference formula into a value as the\\nresult value of the n-dimensional\\ninterpolation. If the parallel processing is used, the efficiency of n-dimensional AD interpolation is almost\\nthe same as that of the one-dimensional AD interpolation. Thus it starts a feasible and convenient approach and provides\\nan effective method for high-dimensional interpolations. Furthermore,\\nif AD interpolation is introduced into machine learning, a new instance-based\\nlearning method is expected to be realized.\",\"PeriodicalId\":23650,\"journal\":{\"name\":\"viXra\",\"volume\":\"47 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"viXra\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36227/TECHRXIV.12552068.V1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"viXra","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36227/TECHRXIV.12552068.V1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximation-Degree-Based Interpolation: A New Interpolation Method
This paper introduces
the measure of approximate-degree and the concept of approximate-degree
function between numerical values, thus developing a new interpolation method
—— approximation-degree-based interpolation, i.e., AD interpolation.
One-dimensional AD interpolation is done directly by using correlative
interpolation formulas; n(n>1)-dimensional AD interpolation is
firstly separated into n parallel
one-dimensional AD interpolation computations to do respectively, and then got
results are synthesized by Sum-Times-Difference formula into a value as the
result value of the n-dimensional
interpolation. If the parallel processing is used, the efficiency of n-dimensional AD interpolation is almost
the same as that of the one-dimensional AD interpolation. Thus it starts a feasible and convenient approach and provides
an effective method for high-dimensional interpolations. Furthermore,
if AD interpolation is introduced into machine learning, a new instance-based
learning method is expected to be realized.