检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:JIA Zhongxiao
机构地区:[1]Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China
出 处:《Science China Mathematics》2004年第z1期222-233,共12页中国科学:数学(英文版)
摘 要:Refined projection methods proposed by the author have received attention internationally. We are concerned with a conventional projection method and its refined counterpart for computing approximations to a simple eigenpair (λ, x) of a large matrix A. Given a subspace ω that contains an approximation to x, these two methods compute approximations (μ,x) and μ,x) to (λ,x), respectively. We establish three results. First, the refined eigenvector approximation or simply the refined Ritz vector x is unique as the deviation of x from ω approaches zero if A is simple. Second, in terms of residual norm of the refined approximate eigenpair (μ, x), we derive lower and upper bounds for the sine of the angle between the Ritz vector x and the refined eigenvector approximation x, and we prove that x≠x unless x = x. Third, we establish relationships between the residual norm ||AX -μx|| of the conventional methods and the residual norm ||Ax -μx|| of the refined methods, and we show that the latter is always smaller than the former if (μ, x) is not an exact eigenpair of A, indicating that the refined projection method is superior to the corresponding conventional counterpart.Refined projection methods proposed by the author have received attention internationally. We are concerned with a conventional projection method and its refined counterpart for computing approximations to a simple eigenpair (λ,x)of a large matrix A. Given a subspace w that contains anapproximation to x, these two methods compute approximations(μ(x~)) and (μ(x^)) to (λ,x),respectively. We establish three results. First, the refinedeigenvector approximation or simply the refined Ritz vector (x^) is unique as the deviation of x from w approaches zero if λ is simple. Second, interms of residual norm of the refined approximate eigenpair (μ,(x^)), we derive lower and upper bounds for the sine of the angle betweenthe Ritz vector (x~) and the refined eigenvector approximation (x^), and we prove that (x~)≠(x^) unless (x^)=x. Third, we establish relationships between theresidual norm ‖A(x~)-μ(x^)‖ of the conventionalmethods and the residual norm ‖A(x^)-μ(x^)‖ of therefined methods, and we show that the latter is always smallerthan the former if (μ,(x^)) is not an exact eigenpair ofA, indicating that the refined projection method is superiorto the corresponding conventional counterpart.
关 键 词:large matrix CONVENTIONAL projection refined projection eigenvalue eigenvector Ritz value Ritz vector refined Ritz vector.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.28