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AN OPTIMAL SELF-SCALING STRATEGY TO THE MODIFIED SYMMETRIC RANK ONE UPDATING

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【作者】 杨月婷徐成贤高岳林

【Author】 Yang Yueting #*, Xu Chengxian #, Gao Yuelin ** # Faculty of Sciences, Xi’an Jiaotong University, Xi’an 710049, China.

【机构】 Faculty of SciencesXi’an Jiaotong UniversityDepartment of Information and Computation Sciencethe Second Northwest Institute for Ethnic Minorities Xi’an 710049ChinaDepartment of MathematicsBeihua UniversityJilin132013ChinaXi’an 710049ChinaYinchuan750021China.

【Abstract】 In the paper, the optimal self-scaling strategy to the modified symmetric rank one (HSR1) update, which satisfies the modified quasi-Newton equation, is derived to improve the condition number of the updates. The scaling factors are derived from minimizing the estimate of upper bounds on the condition number of the updating matrix. Theoretical analysis, and numerical experiments and comparisons show that introducing the optimal scaling factor into the modified symmetric rank one update preserves the positive definiteness of updates, and greatly improves the stability and numerical performance of the modified symmetric rank one algorithm.

【基金】 ThisworkwassupportedbytheNationalNaturalScienceFoundationofChina(No.10231060)
  • 【文献出处】 Academic Journal of Xi’an Jiaotong University ,西安交通大学学报(英文版) , 编辑部邮箱 ,2005年01期
  • 【分类号】O224
  • 【下载频次】59
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