Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing

Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing

The nonlinear compressive sensing (NCS) is an extension of classical compressive sensing (CS) and the iterative hard thresholding (IHT) algorithm is a popular greedy-type method for solving CS. The normalized iterative hard thresholding (NIHT) is a modification of IHT and is more effective than IHT....

Full description

Bibliographic Details
Main Author: Xunzhi Zhu
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2016/2594752
id doaj-dd1d221fd76d45dc9f8e5a429c8b5001
record_format Article
spelling doaj-dd1d221fd76d45dc9f8e5a429c8b50012020-11-24T22:53:45ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/25947522594752Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive SensingXunzhi Zhu0School of Science, Shandong University of Technology, Zibo 255000, ChinaThe nonlinear compressive sensing (NCS) is an extension of classical compressive sensing (CS) and the iterative hard thresholding (IHT) algorithm is a popular greedy-type method for solving CS. The normalized iterative hard thresholding (NIHT) is a modification of IHT and is more effective than IHT. In this paper, we propose an approximately normalized iterative hard thresholding (ANIHT) algorithm for NCS by using the approximate optimal stepsize combining with Armijo stepsize rule preiteration. Under the condition similar to restricted isometry property (RIP), we analyze the condition that can identify the iterative support sets in a finite number of iterations. Numerical experiments show the good performance of the new algorithm for the NCS.http://dx.doi.org/10.1155/2016/2594752
collection DOAJ
language English
format Article
sources DOAJ
author Xunzhi Zhu
spellingShingle Xunzhi Zhu
Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing
Mathematical Problems in Engineering
author_facet Xunzhi Zhu
author_sort Xunzhi Zhu
title Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing
title_short Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing
title_full Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing
title_fullStr Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing
title_full_unstemmed Approximately Normalized Iterative Hard Thresholding for Nonlinear Compressive Sensing
title_sort approximately normalized iterative hard thresholding for nonlinear compressive sensing
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2016-01-01
description The nonlinear compressive sensing (NCS) is an extension of classical compressive sensing (CS) and the iterative hard thresholding (IHT) algorithm is a popular greedy-type method for solving CS. The normalized iterative hard thresholding (NIHT) is a modification of IHT and is more effective than IHT. In this paper, we propose an approximately normalized iterative hard thresholding (ANIHT) algorithm for NCS by using the approximate optimal stepsize combining with Armijo stepsize rule preiteration. Under the condition similar to restricted isometry property (RIP), we analyze the condition that can identify the iterative support sets in a finite number of iterations. Numerical experiments show the good performance of the new algorithm for the NCS.
url http://dx.doi.org/10.1155/2016/2594752
work_keys_str_mv AT xunzhizhu approximatelynormalizediterativehardthresholdingfornonlinearcompressivesensing
_version_ 1725662005774254080

Similar Items