G. Constantinescu, C. Strîmbu, M. Pearsica, L. Miron
{"title":"一种周期现象分析方法","authors":"G. Constantinescu, C. Strîmbu, M. Pearsica, L. Miron","doi":"10.1109/SOFA.2007.4318319","DOIUrl":null,"url":null,"abstract":"This paper is proposing a statistical method, useful for analyzing periodical phenomena whose equations are impossible to be solved analytically. The input data consist in a collection of tabled functions, (numerically determined), named further database. Least square method based algorithms, presented in the first part of the paper, are applied to this database. First, a trigonometric regression algorithm will find the approximating Fourier coefficients. Finally a multiple regression algorithm to fit a polynomial type function is introduced. Its input data are the Fourier coefficients, the Fourier analysis results, or whatever collection of experimental data corresponding to a set of variables. The final part of the paper is dedicated to an example, illustrative for these.","PeriodicalId":205589,"journal":{"name":"2007 2nd International Workshop on Soft Computing Applications","volume":"655 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Method for Periodical Phenomena Analysis\",\"authors\":\"G. Constantinescu, C. Strîmbu, M. Pearsica, L. Miron\",\"doi\":\"10.1109/SOFA.2007.4318319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is proposing a statistical method, useful for analyzing periodical phenomena whose equations are impossible to be solved analytically. The input data consist in a collection of tabled functions, (numerically determined), named further database. Least square method based algorithms, presented in the first part of the paper, are applied to this database. First, a trigonometric regression algorithm will find the approximating Fourier coefficients. Finally a multiple regression algorithm to fit a polynomial type function is introduced. Its input data are the Fourier coefficients, the Fourier analysis results, or whatever collection of experimental data corresponding to a set of variables. The final part of the paper is dedicated to an example, illustrative for these.\",\"PeriodicalId\":205589,\"journal\":{\"name\":\"2007 2nd International Workshop on Soft Computing Applications\",\"volume\":\"655 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 2nd International Workshop on Soft Computing Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOFA.2007.4318319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 2nd International Workshop on Soft Computing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOFA.2007.4318319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper is proposing a statistical method, useful for analyzing periodical phenomena whose equations are impossible to be solved analytically. The input data consist in a collection of tabled functions, (numerically determined), named further database. Least square method based algorithms, presented in the first part of the paper, are applied to this database. First, a trigonometric regression algorithm will find the approximating Fourier coefficients. Finally a multiple regression algorithm to fit a polynomial type function is introduced. Its input data are the Fourier coefficients, the Fourier analysis results, or whatever collection of experimental data corresponding to a set of variables. The final part of the paper is dedicated to an example, illustrative for these.