{"title":"多集分裂可行性问题的CQ算法的强收敛定理","authors":"Yuansheng Guo, Yanrong Yu, Rudong Chen","doi":"10.1109/ICFCSA.2011.21","DOIUrl":null,"url":null,"abstract":"The multiple-set split feasibility problem(MSSFP) was introduced by Censor([9]) is stated as finding a point $x \\in \\cap_N^{i=1}$. such that $Ax \\in \\cap_M^{j=1}Q_j$. where N and M are positive integers, ${C_1,… ,C_N }$ and ${Q_1,… ,Q_M }$ are closed convex subset of Hilbert H1 and H2 , respectively, and A is a linear bounded operator from H1 to H2. MSSFP can be applied to the problem of intensity-modulated radiation therapy in medical care. In this paper, we discuss iterative methods for solving MSSFP in Hilbert spaces. We present modifications of the CQ algorithm in such a way that strong convergence is guaranteed and the limit is a minimum norm solution of MSSFP. Our iterative methods modifies and improves some methods in literature HK Xu(Inverse Problems, vol.20, no.1, pp. 103-120,2004) and FH Wang, HK Xu(Journal of Inequalities and Applications, 2010).","PeriodicalId":141108,"journal":{"name":"2011 International Conference on Future Computer Sciences and Application","volume":"291 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Strong Convergence Theorem of the CQ Algorithm for the Multiple-Set Split Feasibility Problem\",\"authors\":\"Yuansheng Guo, Yanrong Yu, Rudong Chen\",\"doi\":\"10.1109/ICFCSA.2011.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The multiple-set split feasibility problem(MSSFP) was introduced by Censor([9]) is stated as finding a point $x \\\\in \\\\cap_N^{i=1}$. such that $Ax \\\\in \\\\cap_M^{j=1}Q_j$. where N and M are positive integers, ${C_1,… ,C_N }$ and ${Q_1,… ,Q_M }$ are closed convex subset of Hilbert H1 and H2 , respectively, and A is a linear bounded operator from H1 to H2. MSSFP can be applied to the problem of intensity-modulated radiation therapy in medical care. In this paper, we discuss iterative methods for solving MSSFP in Hilbert spaces. We present modifications of the CQ algorithm in such a way that strong convergence is guaranteed and the limit is a minimum norm solution of MSSFP. Our iterative methods modifies and improves some methods in literature HK Xu(Inverse Problems, vol.20, no.1, pp. 103-120,2004) and FH Wang, HK Xu(Journal of Inequalities and Applications, 2010).\",\"PeriodicalId\":141108,\"journal\":{\"name\":\"2011 International Conference on Future Computer Sciences and Application\",\"volume\":\"291 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Future Computer Sciences and Application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFCSA.2011.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Future Computer Sciences and Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFCSA.2011.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Strong Convergence Theorem of the CQ Algorithm for the Multiple-Set Split Feasibility Problem
The multiple-set split feasibility problem(MSSFP) was introduced by Censor([9]) is stated as finding a point $x \in \cap_N^{i=1}$. such that $Ax \in \cap_M^{j=1}Q_j$. where N and M are positive integers, ${C_1,… ,C_N }$ and ${Q_1,… ,Q_M }$ are closed convex subset of Hilbert H1 and H2 , respectively, and A is a linear bounded operator from H1 to H2. MSSFP can be applied to the problem of intensity-modulated radiation therapy in medical care. In this paper, we discuss iterative methods for solving MSSFP in Hilbert spaces. We present modifications of the CQ algorithm in such a way that strong convergence is guaranteed and the limit is a minimum norm solution of MSSFP. Our iterative methods modifies and improves some methods in literature HK Xu(Inverse Problems, vol.20, no.1, pp. 103-120,2004) and FH Wang, HK Xu(Journal of Inequalities and Applications, 2010).