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Algorithms 2017, 10(1), 29; doi:10.3390/a10010029

Stable Analysis of Compressive Principal Component Pursuit

1,2,* and 2
1
School of Computer Science, Civil Aviation Flight University of China, Guanghan 618307, China
2
School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Academic Editor: Bruno Carpentieri
Received: 5 January 2017 / Revised: 10 February 2017 / Accepted: 17 February 2017 / Published: 21 February 2017
View Full-Text   |   Download PDF [256 KB, uploaded 21 February 2017]   |  

Abstract

Compressive principal component pursuit (CPCP) recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. Pervious works mainly focus on the analysis of the existence and uniqueness. In this paper, we address its stability. We prove that the solution to the related convex programming of CPCP gives an estimate that is stable to small entry-wise noise. We also provide numerical simulation results to support our result. Numerical results show that the solution to the related convex program is stable to small entry-wise noise under board condition. View Full-Text
Keywords: matrix completion; low-complexity structure; stability analytic; compressive principal component pursuit matrix completion; low-complexity structure; stability analytic; compressive principal component pursuit
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You, Q.; Wan, Q. Stable Analysis of Compressive Principal Component Pursuit. Algorithms 2017, 10, 29.

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