Improved Sampling and Reconstruction in Spline Subspaces

被引：1
|
作者：
Xian, Jun [1 ,2 ]
Li, Song [3 ]
机构：
[1] Sun Yat Sen Univ, Dept Math, Guangzhou 510275, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Guangdong Prov Key Lab Computat Sci, Guangzhou 510275, Guangdong, Peoples R China
[3] Zhejiang Univ, Dept Math, Hangzhou 310027, Zhejiang, Peoples R China
来源：
ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2016年 / 32卷 / 02期
基金：
中国国家自然科学基金;
关键词：
irregular sampling; iterative algorithm; error estimate; spline subspace; SHIFT-INVARIANT SPACES; APPROXIMATION; THEOREMS;
D O I：
10.1007/s10255-016-0570-0
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
As a special shift-invariant spaces, spline subspaces yield many advantages so that there are many practical applications for signal or image processing. In this paper, we pay attention to the sampling and reconstruction problem in spline subspaces. We improve lower bound of sampling set conditions in spline subspaces. Based on the improved explicit lower bound, a improved explicit convergence ratio of reconstruction algorithm is obtained. The improved convergence ratio occupies faster convergence rate than old one. At the end, some numerical examples are shown to validate our results.
引用
收藏
页码：447 / 460
页数：14
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