Restricted Isometry Property of Principal Component Pursuit with Reduced Linear Measurements
The principal component prsuit with reduced linear measurements (PCP_RLM) has gained great attention in applications, such as machine learning, video, and aligning multiple images. The recent research shows that strongly convex optimization for compressive principal component pursuit can guarantee t...
Saved in:
Main Authors: | Qingshan You, Qun Wan, Haiwen Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2013-01-01
|
Series: | Journal of Applied Mathematics |
Online Access: | http://dx.doi.org/10.1155/2013/959403 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A note on orthogonal matching pursuit under restricted isometry property
by: Xueping Chen, et al.
Published: (2022-05-01) -
Restricted p-Isometry Properties of Partially Sparse Signal Recovery
by: Haini Bi, et al.
Published: (2013-01-01) -
A Stochastic Restricted Principal Components Regression Estimator in the Linear Model
by: Daojiang He, et al.
Published: (2014-01-01) -
A note on finite codimensional linear isometries of C(X) into C(Y)
by: Sin-Ei Takahasi, et al.
Published: (1995-01-01) -
Isometries of a function space
by: U. D. Vyas
Published: (1987-01-01)