检索结果-南通市图书馆

Iterative implementation of the adaptive regularization yields optimality

science china mathematics 2005年第4期48卷 485-492页

作者： ma qinghua & wang yanfei department of information sciences, college of arts and science of beijing union university, beijing 10003., china National Key Laboratory on Remote Sensing science, Institute of Remote Sensing Applications, Chinese Academy of sciences, beijing 100101, china department of mathematics, university of Central Florida, P. O. Box 161364, Orlando, FL 32816-1364, USA department of information sciences College of Arts and Science of Beijing Union University Beijing China National Key Laboratory on Remote Sensing science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China

The adaptive regularization method is first proposed by Ryzhikov et al. for the deconvolution in elimination of multiples. This method is stronger than the Tikhonov regularization in the sense that itis adaptive, i.e. it eliminates the small eigenvalues of theadjoint operator when it is nearly singular. We will show in this paper that the adaptive regularization can be implemented iterately. Some properties of the proposed non-stationary iterated adaptive regularization method are analyzed. The rate of convergence for inexact data is proved. Therefore the iterative implementation of the adaptive regularization can yield optimality.

关键词： ill-posed problems, non-stationary iterated adaptive regularization, optimality.

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Chapter 9 Full Space and Subspace Methods for Large Scale Image Restoration

Chapter 9 Full Space and Subspace Methods for Large Scale Im...

引用

中国科学院地质与地球物理研究所第十届(2010年度)学术年会

作者： yanfei wang Institute of Geology and Geophysics,Chinese Academy of sciences,beijing 100029,china. Shiqian ma department of Industrial Engineering and Operations Research,Columbia university, New York,NY 10027-6902,USA. qinghua ma~(1,2) 1 School of information,Renmin university of china,beijing,100872,china. 2 college of Art and science,beijing union university,beijing,100083,china.

In this chapter,we discuss about the full space and subspace methods for ill-posed image restoration *** restoration refers to minimizing the degradation which is caused by sensing environment,say CCD camera misfocus, nonuniform motion,atmospheric aerosols and atmospheric *** image restoration problems,a key matter is to solve a quadratic programming *** study numerical solution methods in full space by limited memory of BFGS method and the subspace trust region *** develop a novel approach for reducing the cost of sparse matrix-vector multiplication when applying the full space and subspace methods to atmospheric image *** the projection technique for the regularized convex quadratic functional is developed in the iteration for ensuring *** experiments indicate that these methods are useful for large-scale image restoration problems.

关键词：

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：