Hybrid methods for approximating Hankel matrix

被引：10

作者：

Al-Homidan, S ^{[1
]}

机构：

[1] King Fahd Univ Petr & Minerals, Dept Math Sci, Dhahran 31261, Saudi Arabia

来源：

NUMERICAL ALGORITHMS | 2003年 / 32卷 / 01期

关键词：

alternating projections; Hankel matrix; least distance functions; non-smooth optimization; positive semi-definite matrix; Newton method;

D O I：

10.1023/A:1022202125077

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Hybrid methods for minimizing least distance functions with Hankel positive semi-definite matrix constraints are considered. Our approach is based on (i) a projection algorithm which converges globally but slowly; and (ii) the Newton method which is faster. Hybrid methods that attempt to combine the best features of both methods are then considered. Comparative numerical results are reported.

引用

页码：57 / 66

页数：10

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