Next Article in Journal
An Improved Multi-Objective Artificial Bee Colony Optimization Algorithm with Regulation Operators
Previous Article in Journal
A Quick Artificial Bee Colony Algorithm for Image Thresholding
Article Menu

Export Article

Open AccessArticle
Information 2017, 8(1), 17; doi:10.3390/info8010017

Exact Solution Analysis of Strongly Convex Programming for Principal Component Pursuit

School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Received: 14 October 2016 / Accepted: 25 January 2017 / Published: 2 February 2017
(This article belongs to the Section Information Theory and Methodology)
View Full-Text   |   Download PDF [254 KB, uploaded 24 March 2017]   |  

Abstract

In this paper, we address strongly convex programming for principal component analysis, which recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. In this paper, we firstly provide sufficient conditions under which the strongly convex models lead to the exact low-rank matrix recovery. Secondly, we also give suggestions that will guide us how to choose suitable parameters in practical algorithms. Finally, the proposed result is extended to the principal component pursuit with reduced linear measurements and we provide numerical experiments. View Full-Text
Keywords: low-complexity structure; strongly convex programming; principal component pursuit; reduced linear measurements low-complexity structure; strongly convex programming; principal component pursuit; reduced linear measurements
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

You, Q.; Wan, Q. Exact Solution Analysis of Strongly Convex Programming for Principal Component Pursuit. Information 2017, 8, 17.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Information EISSN 2078-2489 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top