{"title":"反馈导向动态积分划分","authors":"S. Tabirca, T. Tabirca, L. Yang, Len Freeman","doi":"10.1109/ISPDC.2006.26","DOIUrl":null,"url":null,"abstract":"In this article we introduce a new iterative method for integral partition called the feedback guided dynamic integral partition (FGDIP) algorithm. The problem to study is the partition of a definite integral into p identical sub-integrals. The method generates iteratively a sequence of integral bounds by re-balancing the previous integral partition to achieve a better one. A simple convergence condition is also proposed. Experimental results show that the proposed method FGDIP achieves better performance than the classical Newton's method","PeriodicalId":196790,"journal":{"name":"2006 Fifth International Symposium on Parallel and Distributed Computing","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Feedback Guided Dynamic Integral Partition\",\"authors\":\"S. Tabirca, T. Tabirca, L. Yang, Len Freeman\",\"doi\":\"10.1109/ISPDC.2006.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article we introduce a new iterative method for integral partition called the feedback guided dynamic integral partition (FGDIP) algorithm. The problem to study is the partition of a definite integral into p identical sub-integrals. The method generates iteratively a sequence of integral bounds by re-balancing the previous integral partition to achieve a better one. A simple convergence condition is also proposed. Experimental results show that the proposed method FGDIP achieves better performance than the classical Newton's method\",\"PeriodicalId\":196790,\"journal\":{\"name\":\"2006 Fifth International Symposium on Parallel and Distributed Computing\",\"volume\":\"109 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 Fifth International Symposium on Parallel and Distributed Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDC.2006.26\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Fifth International Symposium on Parallel and Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPDC.2006.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this article we introduce a new iterative method for integral partition called the feedback guided dynamic integral partition (FGDIP) algorithm. The problem to study is the partition of a definite integral into p identical sub-integrals. The method generates iteratively a sequence of integral bounds by re-balancing the previous integral partition to achieve a better one. A simple convergence condition is also proposed. Experimental results show that the proposed method FGDIP achieves better performance than the classical Newton's method
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