# NORST-rmc

**Repository Path**: Arhatking/NORST-rmc

## Basic Information

- **Project Name**: NORST-rmc
- **Description**: Robust Subspace Tracking and Matrix Completion Algorithm
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-01-17
- **Last Updated**: 2020-12-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

This folder contains the code accompanying the following paper -to appear, IEEE Transactions on Signal Processing (2019).

	[1] "Subspace Tracking from Missing and Outlier Corrupted Data"
	     Praneeth Narayanamurthy, Vahid Daneshpajooh, and Namrata Vaswani
	     arXiv:1810.03051v2 [cs.LG] 30 May 2019

List of main files:

	1. wrapper_NORSTmiss_fixedsubspace.m : wrapper containing the simulated data experiments for NORST-miss in fixed Subspace
	2. wrapper_NORSTmiss_changingsubspace.m : wrapper containing the simulated data experiments for NORST-miss in changing Subspace
	3. wrapper_NORSTmissrob_simulateddata.m : wrapper containing the simulated data experiments for NORST-miss-rob
	4. wrapper_NORSTsampeff.m : wrapper containing the simulated data experiments for NORST-samp-eff
	5. wrapper_VideoAnalysis.m  : wrapper for background recovery in videos.
	6. NORST.m       : main function which implements the NORST-miss-robust algorithm for subspace tracking (on simulated data)
	7. NORST_random.m: main function which implements the NORST-miss algorithm for subspace tracking (on simulated data)
	8. NORST_video.m : main function which implements the NORST-miss-robust algorithm for background recovery (real data-video)


Folders:

	YALL1 : folder containing files to implement ell-1 minimization.
	PROPACK : Linear Algebra toolbox for MATLAB
	data : folder containing several video data matrices for the task of background recovery

Other files:

	ncrpca : code implemented Non-convex Robust PCA, NIPS 14 downloaded from authors' website and its accompaniments lansvd, lanbpro etc
	cgls : fast method to implement least squares
	simpleEVD : simple Eigen Value Decomposition
	Calc_SubspaceError : it calculates the distance between two subspaces

For any further questions/suggestions please contact us @ vahidd/pkurpadn [at] iastate [dot] edu