Selected Publications on Sparse Matrix Transform:
Covariance Estimation and Signal Analysis
Powerpoint and Video:
Powerpoint Slides describing SMT Covariance Estimation
Movie of estimated covariance as K increases
(Courtesy of James Theiler at LANL); What is this?
Movie of (correlation)^2 as K increases
(Courtesy of James Theiler at LANL); What is this?
Matlab Software:
Matlab Software for SMT Covariance Estimation
(Special version for Windows Matlab Version 6 )
Matlab Software for Fast SMT Design using Graphical Neighborhood Constraint (ICASSP 2010)
Matlab Software for SMTLASSO Regression (ICASSP 2010)
Journal Publications:

pdf
Guangzhi Cao, Leonardo R. Bachega, and Charles A. Bouman,
``The Sparse Matrix Transform for Covariance Estimation and Analysis of High Dimensional Signals,''
pp. 625640,
vol. 20, no. 3, {\em IEEE Trans. on Image Processing,}
March 2011.

pdf
James Theiler, Gaungzhi Cao, Leonardo R. Bachega, Charles A. Bouman,
``Sparse Matrix Transform for Hyperspectral Image Processing,''
vol. 5, no. 3, {\em IEEE Selected Topics in Signal Process,}
June 2011.
Conference Publications:

paper
and
slides
Leonardo R. Bachega, Srikanth Hariharan, Charles A. Bouman, and Ness Shroff,
``Distributed Signal Decorrelation in Wireless Sensor Networks using the Sparse Matrix Transform,''
Proceedings of {\em SPIE Conference on Independent Component Analysis, Wavelets,
Neural Networks, Biosystems, and Nanoengineering IX},
vol. 8058, April 2729, 2011.

pdf
Srikanth Hariharan, Leonardo R. Bachega, Ness B. Shroff, and Charles A. Bouman,
``Communication efficient signal detection in correlated clutter for wireless sensor networks,''
{\em Asilomar Conference on Signals, Systems and Computers,}
pp. 14271431, 2010.

pdf
J. Theiler, G. Cao, and C. A. Bouman. "Sparse matrix transform for
fast projection to reduced dimension,"
p 43625, Proc. IGARSS (2010) 43624365.

pdf
Leonardo R. Bachega, Guangzhi Cao, and Charles A. Bouman,
``Fast Signal Analysis and Decomposition on Graphs using the Sparse Matrix Transform,''
in the Proceedings of the {\em International Conference on Acoustic, Speech, and Signal Processing (ICASSP)},
March 1419, 2010.

pdf
Guangzhi Cao, Yandong Guo, and Charles A. Bouman,
``High Dimensional Regression using the Sparse Matrix Transform (SMT),''
in the Proceedings of the {\em International Conference on Acoustic, Speech, and Signal Processing (ICASSP)},
March 1419, 2010.

pdf
Guangzhi Cao, Charles A. Bouman, and James Theiler
``Weak Signal Detection in Hyperspectral Imagery Using Sparse Matrix Transform (SMT) Covariance Estimation,''
{\em Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009, WHISPERS '09,}
Grenoble France, August 26  August 28, 2009.

pdf
Guangzhi Cao and Charles A. Bouman,
``Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform,''
Proceedings of {\em Neural Information Processing Systems Conference},
December, 2008.

pdf
Guangzhi Cao and Charles A. Bouman,
``Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform,''
Technical Report TRECE0805,
School of Electrical and Computer Engineering,
Purdue University, April 2008.
Fast NonIterative MAP Reconstruction

pdf
Guangzhi Cao, Charles A. Bouman, and Kevin J. Webb,
``NonIterative MAP Reconstruction Using Sparse Matrix Representations''
{\em IEEE Transactions on Image Processing,}
pp. 20852099, vol. 18, no. 9, September 2009.

pdf
Jianing Wei, Guangzhi Cao, Charles A. Bouman, and Jan P. Allebach,
``Fast Spacevarying Convolution and Its Application in Stray Light Reduction''
{\em Proceedings of the SPIE/IS\&T Conf. on Computational Imaging VII,}
January 1920, 2009.

pdf
Guangzhi Cao, Charles A. Bouman, Kevin J. Webb,
``Fast Reconstruction Algorithms for Optical Tomography using Sparse Matrix Representation''
{\bf (invited paper)},
{\em International Symposium on Biomedical Imaging,}
April 14, 2007.

pdf
G. Cao, C. A. Bouman, and K. J. Webb,
``Fast and Efficient Stored Matrix Techniques for Optical Tomography,''
{\bf (invited paper)},
{\em Fortieth Asilomar Conference on Signals, Systems and Computers,}
pp. 156160,
Pacific Grove CA, Oct. 29  Nov. 1, 2006.
Acknowledgment of Support
This work was supported by the Army Research Office under Proposal 56541CI
and the National Science Foundation under Contract CCR0431024.