A New Method for Large Scale Nonnegative Least Squares Problems

Author

Yong, Longquan

Author_Institution

Dept. of Math., Shaanxi Univ. of Technol., Hanzhong, China

Volume

2

fYear

2009

fDate

13-15 Nov. 2009

Firstpage

448

Lastpage

450

Abstract

We present a new method for solving large scale nonnegative least squares problems. Firstly, nonnegative least squares problem was transformed into monotone linear complementarity problem. Then we apply potential-reduction interior point algorithm to monotone linear complementarity problem which is based on the Newton direction and centering direction. We show that this algorithm have the polynomial complexity. Numerical results are reported which demonstrate very good computational performance on nonnegative least squares problems.

Keywords

Newton method; computational complexity; least squares approximations; polynomials; Newton direction; centering direction; computational performance; large scale nonnegative least squares problems; monotone linear complementarity problem; polynomial complexity; potential-reduction interior point algorithm; Convergence; Design optimization; Large-scale systems; Least squares methods; Mathematical programming; Mathematics; Polynomials; Quadratic programming; Vectors; large scale nonnegative least squares problem; monotone linear complementarity problem; polynomial complexity; potential-reduction interior point algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Technology and Development, 2009. ICCTD '09. International Conference on

Conference_Location

Kota Kinabalu

Print_ISBN

978-0-7695-3892-1

Type

conf

DOI

10.1109/ICCTD.2009.88

Filename

5360187