Software for Recent Research

 

Most code is also available from these links

·        Please cite the relevant papers listed below when you use any of this code

·        http://www.ece.iastate.edu/~namrata/research/SequentialCS.html#codear

·        http://www.ece.iastate.edu/~chenlu/ReProCS/ReProCS_main.htm

 

 

·        Modified-CS

o   Please cite following papers when you use this code

§   Namrata Vaswani and Wei Lu, Modified-CS: Modifying Compressive Sensing for Problems with Partially Known Support,   IEEE Trans. Signal Processing, Vol. 58, No. 9, September, 2010. Shorter version in ISIT 2009.

§  Wei Lu, Taoran Li, Ian Atkinson,  Namrata Vaswani Modified-CS-Residual for Recursive Reconstruction of Highly Undersampled Functional MRI Sequences, IEEE Intl. Conf. Image Proc. (ICIP) 2011

§  Wei Lu and Namrata Vaswani, Regularized Modified BPDN for Noisy Sparse Reconstruction with Partial Erroneous Support and Signal Value Knowledge, IEEE Trans. Signal Processing, Vol. 60, No. 1, January, 2012

§  Wei Lu and Namrata Vaswani, Exact Reconstruction Conditions for Regularized Modified Basis Pursuit, IEEE Trans. Signal Processing, vol. 60, No. 5, May, 2012

o   Code:

§  Code using CVX (works for signals/images of size upto about 4096: 

·         Download Code from here (Wei Lu's page)

§  Code for large-sized images (optimization code rewritten using fast operators for 2D-DFT and 2D-DWT) 

·         Download Code from here (Wei Lu's page)

§  A note about ModifiedCS_sequential.m 

·         the following may appear as a small typo: for seq=1:seqlen should be replaced by for seq=2:seqlen but it does not affect results in any way for sparse sequences, it actually improves results for compressible sequences.

·        Kalman filtered Compressed Sensing (KF-CS) and Least Squares CS (LS-CS)

o   Please cite following papers when you use this code

§   Namrata Vaswani, LS-CS-residual (LS-CS): Compressive Sensing on the Least Squares Residual, IEEE Trans. Signal Processing, Vol. 58, No. 8, August, 2010.

§   Namrata Vaswani, Kalman Filtered Compressed Sensing, IEEE Intl. Conf. Image Proc. (ICIP), 2008.

§  Chenlu Qiu, Wei Lu and Namrata Vaswani, Real-time Dynamic MR Image Reconstruction using Kalman Filtered Compressed Sensing, IEEE Intl. Conf. Acous. Speech. Sig. Proc. (ICASSP), 2009.

§  Namrata Vaswani, Analyzing Least Squares and Kalman Filtered Compressed Sensing, IEEE Intl. Conf. Acous. Speech. Sig. Proc. (ICASSP), 2009.

o   Code:

§  Code: LSCS_KFCS_code.zip

·         Contains LS-CSresidual-LS (LS-CS),  KF-CSresidual-LS (KF-CS), KF-CSresidual-KF (KF-CS - 0), versions with and without deletion step

·         README.txt with detailed comments and instructions

§  Two older versions of KF-CS code

·         Kalman filtered CS (KF-CS): KFCS_new.zip  (Main file: runsims_final, see comments and see README.txt)

·         Please cite N. Vaswani, ICASSP'09 and ICIP'08 if you use this code.

·         See README.txt for code structure. runsims_final.m is the main file. kfcs_full contains the kfcs code.

·         Least Squares CS (LS-CS): Replace the KF in the above code by LS: to get the LS-CS implementation (will be posted soon)

§  Older version of code based on the ICIP'08 paper:

·         Code: KFCS.zip (To run it: runsims2, followed by plotting the errors)

·         Please cite the above ICIP paper when using this code

·         See README.txt or comments in runsims2.m

·         You may need to install netlab and add it to your MATLAB path: netlab.zip

·         Recursive Projected CS or ReProCS for Recursive Robust PCA or Recursive Sparse Recovery in Large but Structured Noise

o   Please cite the following papers when you use this code

§   Chenlu Qiu and Namrata VaswaniReal-time Robust Principal Components' Pursuit, Allerton, 2010

§  Chenlu Qiu and Namrata Vaswani, Recursive Sparse Recovery in Large but Correlated Noise, Allerton 2011

§  Chenlu Qiu and Namrata Vaswani, Recursive Sparse Recovery in Large but Structured Noise - Part 2, IEEE Intl. Symp. Info. Theory (ISIT) 2013

§  Chenlu Qiu, Namrata Vaswani, Brian Lois and Leslie Hogben, Recursive Robust PCA or Recursive Sparse Recovery in Large but Structured Noise, revised and resubmitted to IEEE Transactions on Information Theory

o   Code:

§  Download from Chenlu Qiu’s webpage: link

·         Older work

o   Code for my older work is obtained by following this link: http://www.ece.iastate.edu/~namrata/research/research.html