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
收藏
页码：57 / 66
页数：10
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