**Bob Plemmons is an author of more than 250 articles and books on computational mathematics. He has served on the editorial boards of seven journals.**

**Nonnegative Matrices in the Mathematical Sciences (link in Amazon), by Abraham Berman and R.J.Plemmons. Book **

*For scientists and engineers who use or work with theory and computation associated with practical problems relating to Markov chains and queuing networks, economic analysis, or mathematical programming. Originally published in 1979, this new edition adds material that updates the subject relative to developments from 1979 to 1993. Theory and applications of nonnegative matrices are blended here, and extensive references are included in each area.*

**Description**:

*Series: Classics in Applied Mathematics (Book 9), Publisher: Society for Industrial and Applied Mathematics.**See Robert Plemmons’ Google Scholar Citations page referencing over 17,000 citations since 1962. **Also see Robert Plemmons Computer Science Bibliography page, compiled by Trier University, Germany.*

**List of Publications by R. J. Plemmons, 2020 – 1965:**

A two-stage method for spectral-spatial classification of hyperspectral images. R.Chan, K. Kan and R. Plemmons. Published in the Journal of Mathematical Imaging and Vision, 2020. Link: https://arxiv.org/pdf/1806.00836.pdf

Joint 3D localization and classification of space debris using a multispectral rotating point spread function. C. Wang, G. Ballad, R. Plemmons, and S. Prasad. Optical Soc. of Amer. Journal on Applied Optics, vol 58, No. 31, 2019. Links: https://doi.org/10.1364/AO.58.008598 or https://arXiv.org/pdf/1906.04749.pdf

Nonconvex optimization for 3D point source localization using a rotating point spread function, Chao Wang, Raymond Chan, Mila Nikolova, Robert Plemmons, and Sudhakar Prasad. Submitted to SIAM J. Imaging Sciences 04/01/2018. (pdf file)

Multi-Dimensional Regular Expressions for Object Detection, T. Torgersen, P. Pauca, R. Plemmons, D. Nikic, J. Wu and R. Rand. Proc. Conf. on Imaging, Vision and Learning based on Optimization and PDEs, Bergen, Norway, 2016. Published in Springer’s Mathematics and Visualization, Series, 2018. (pdf file)

Individual-Specific, Sparse Inverse Covariance Estimation in Generalized Estimating Equations, Q. Zhang, E. Ip, J. Pan, and R. Plemmons. Statistics and Probability Letters 122 (2017), 96-103. (pdf file)

Classification of Pixel-Level Fused Hyperspectral and LiDAR Data Using Deep Convolutional Neural Networks, S. Morchhale, P. Pauca, R. Plemmons, and T. Torgersen.Proc. IEEE Conf. on Hyperspectral Imaging (WHISPERS), Los Angeles, 2016. (pdf file)

Trust-Region Methods for Nonconvex Sparse Recovery Optimization, L. Adhikari J. Erway, R. Marcia and R. Plemmons, Proc. ISITA, IEEE, XPlore, 2016. (pdf file)

Deblurring and Sparse Unmixing of Hyperspectral Images using Multiple Point Spread Functions, S. Berisha, J. Nagy and R. Plemmons. Published in SIAM J. Scientific Computing: 2015. (pdf file)

Estimation of Atmospheric PSF Parameters for Hyperspectral Imaging, S. Berisha, J. Nagy and R. Plemmons. Published in: Numerical Lin. Alg. and Applic., 2015. (pdf file)

Information-Theoretic Feature Selection for Classification: Applications to Fusion of Hyperspectral and LiDAR Data, Q. Zhang, P. Pauca, R. Plemmons, R. Rand and T. Torgersen. Working paper, 2014. (pdf file)

Image Reconstruction from Double Random Projection, Q. Zhang and R. Plemmons. Published in: IEEE Trans. Image Processing, 2014. (pdf file)

Detecting Objects under Shadows by Fusion of Hyperspectral and LiDAR Data: A Physical Model Approach, Q. Zhang, P. Pauca and R. Plemmons. Published in: Proc. IEEE WHISPERS Conference on Hyperspectral Imaging, 2013. (pdf file)

Randomized Methods in Lossless Compression of Hyperspectral Data, Q. Zhang, P. Pauca and R. Plemmons. Published in: SPIE Journal of Applied Remote Sensing, 2013: http://dx.doi.org/10.1117/1.JRS.7.074598. (pdf file)

Deblurring and Sparse Unmixing For Hyperspectral Images, X. Zhao, F. Wang, T. Huang, M. Ng and R. Plemmons. Published in: IEEE Trans. on Geoscience and Remote Sensing, 2013. (pdf file)

Joint Multiframe Blind Deconvolution and Spectral Unmixing of Hyperspectral Images, Q. Zhang, P. Pauca and R. Plemmons. Published in: Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS Tech. 2013), Maui, HI. (pdf file)

Shape and Pose Recovery of Solar-Illuminated Surfaces from Compressive Spectral-Polarimetric Image Data, S. Prasad, Q. Zhang and R. Plemmons. Published in: Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS Tech. 2013), Maui, HI. (pdf file)

Randomized SVD Methods in Hyperspectral Imaging, J. Zhang, J. Erway, X. Hu, Q. Zhang and R. Plemmons. Published in: J. Electrical and Computer Engineering, Special Issue on Spectral Imaging, Volume 2012, Article ID 409357, 15 pages, September, 2012. (pdf file)

A Novel Approach To Environment Reconstruction In LIDAR and HSI Datasets, D. Nikic, P. Pauca, R. Plemmons J. Wu, P. Zhang. Published in: Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS Tech. 2012), Maui, HI. (pdf file)

Sparse Nonnegative Matrix Underapproximation and Its Application to Hyperspectral Image Analysis, N. Gillis and R. Plemmons. Published in: Linear Algebra and its Applications, 2012 . (pdf file)

Priors in Sparse Recursive Decompositions of Hyperspectral Images, N. Gillis, R. Plemmons and Q. Zhang. Proc. SPIE Conf. on Defense, Security and Sensing, April, 2012. (pdf file)

Iterative Directional Ray-based Iris Segmentation for Challenging Periocular Images, X. Hu, P. Pauca and R. Plemmons. Published in: Biometric Recognition, December 2011, LNCS7098, Springer. (pdf file)

An Evaluation of Iris Segmentation Algorithms in Challenging Periocular Images, R. Jillela, A. Ross, N. Boddeti, B. Vijaya Kumar, X. Hu, R. Plemmons, P. Pauca. Chapter in Handbook of Iris Recognition, Eds. Burge, M., Bowyer, K., Springer, Preprint, August, 2011, to appear January (2012). (pdf file)

Joint Segmentation and Reconstruction of Hyperspectral Data with Compressed Measurements, Q. Zhang, R. Plemmons, D. Kittle, D. Brady and S. Prasad. Published in: Applied Optics, July 2011. (pdf file)

Reconstructing and Segmenting Hyperspectral Images from Compressed Measurements, Q. Zhang, R. Plemmons, D. Kittle, D. Brady and S. Prasad. Published in: Proc. SPIE Conf. on Defense, Security and Sensing, 2011. (pdf file)

Dimensionality Reduction, Classification, and Spectral Mixture Analysis using Nonnegative Underapproximation, N. Gillis and R. Plemmons. Published in: Optical Engineering, Feb., 2011. (pdf file)

Matching Highly Non-ideal Ocular Images: An Information Fusion Approach, Arun Ross, Raghavender Jillela (West Virginia University) Jonathon M. Smereka, Vishnu Naresh Boddeti, B. V. K. Vijaya Kumar (Carnegie Mellon University) Ryan Barnard, Xiaofei Hu, Paul Pauca, Robert Plemmons (Wake Forest University), December, 2011. (pdf file)

Coupled Segmentation and Denoising/Deblurring Models for Hyperspectral Material Identification, F. Li, M. Ng, and R. Plemmons. Published in: Num. Lin. Alg. Applic., 2011. (pdf file)

A Hybrid Multilevel-Active Set Method for Large Box-Constrained Discrete Ill-Posed Inverse Problems, S. Morigi, R. Plemmons, L. Reichel, and F. Sgallari. Published in: Colcolo – Numerical and Computational Mathematics, 2011. (pdf file)

Matrix Structures and Parallel Algorithms for Image Superresolution Reconstruction, Q. Zhang, R. Guy, and R. Plemmons. Published in: SIAM J. Matrix Analysis and Applic., 2010. (pdf file)

Hyperspectral Image Segmentation, Deblurring, and Spectral Analysis, F. Li, M. Ng, R. Plemmons, S. Prasad, P. Zhang. Published in: Proc. SPIE Conf. on Defense, Security, and Sensing, Orlando, 2010.

A Practical Enhanced-Resolution Integrated Optical-Digital Imaging Camera (PERIODIC), M. Mirotznik, S. Mathews, R. Plemmons, P. Pauca, T. Torgersen, R. Barnard, B. Gray, T. Guy, Q. Zhang J. van der Gracht, C. Petersen, M. Bodnar, and S. Prasad. Proc. Annual SPIE Conf. on Defense, Security and Sensing, Orlando, April 2009.

Line-source Based X-ray Tomography, D. Bharkhada, H. Yu, H. Liu, R. Plemmons and G. Wang. Published in International J. Biomedical Engineering, 2009. (pdf file)

Pupil Phase Encoding for Multi-Aperture Imaging, P. Pauca, J. van der Gracht, R. Plemmons, S. Prasad, and T. Torgersen. Proc. Annual SPIE Meeting, San Diego, August 2008. (pdf file)

Tensor Methods for Hyperspectral Data Analysis: A Space Object Material Identification Study, Q. Zhang, H. Wang, R. Plemmons and P. Pauca. Appeared in J. Optical Soc. Amer. A, Dec. 2008. (pdf file)

Nonnegativity Constraints in Numerical Analysis, D. Chen and R. Plemmons. Paper presented at the Symposium on the Birth of Numerical Analysis, Leuven Belgium, October 2007. Published by World Scientific Press, A. Bultheel and R. Cools, Eds. (2009) (pdf file)

PERIODIC: Integrated Computational Array Imaging Technology, R. Plemmons, S. Prasad, S. Mathews, M. Mirotznik, R. Barnard, B. Gray, P. Pauca, T. Torgersen, J. van der Gracht, Greg Behrmann. Extended abstract for invited paper at the Conference on Computational Optical Sensing and Imaging (COSI), in Vancouver June 2007. (pdf file)

Novel Multi-layer Nonnegative Tensor Factorization with Sparsity Constraints, Andrzej Cichocki, Rafal Zdunek, Seungjin Choi, Robert Plemmons, and Shun-ichi Amari. Appeared in Proc. of the 8th International Conference on Adaptive and Natural Computing Algorithms, Warsaw, Poland, April 2007. (pdf file)

Nonnegative Tensor Factorization using Alpha and Beta Divergencies, Andrzej Cichocki, Rafal Zdunek, Seungjin Choi, Robert Plemmons, and Shun-ichi Amari. Appeared in Proc. of the 32nd International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, April 2007. (pdf file)

Blind Deconvolution and Structured Matrix Computations with Applications to Array Imaging, Michael Ng and Robert Plemmons. Invited Chapter written for the book “Blind Deconvolution: Theory and Applications”, P. Campisi and K. Egiazarian, Editors, CRC Press, pp. 377-418, 2007. (pdf file)

High-Resolution Iris Image Reconstruction from Low-Resolution Imagery, R. Barnard, P. Pauca, T. Torgersen, R. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Matthews, M. Mirotznik. Appeared in Proc. SPIE Annual Meeting, San Diego, 2006.

Algorithms and Applications for Approximate Nonnegative Matrix Factorization, Michael Berry, Murray Browne, Amy Langville, Paul Pauca, and Robert Plemmons. Appeared in Computational Statistics & Data Analysis 52(1): 155-173 (2007). (pdf file)

A Computational Method for the Restoration of Images with an Unknown, Spatially-Varying Blur, John Bardsley, Stuart Jefferies, James Nagy, and Robert Plemmons. Appeared in Optics Express, Vol. 14, No. 5, pp. 1767-1782, March 2006. (pdf file)

Nonnegative Matrix Factorization for Spectral Data Analysis, Paul Pauca, Jon Piper, and Robert Plemmons. Appeared in Linear Algebra and Applications, Vol. 416, pp. 29-47, 2006. (pdf file)

Iterative Signal and Image Deconvolution for Estimation of the Complex Medium Response, Zhiping Mu, Robert Plemmons, and Pete Santago. Appeared in the International Journal on Imaging Systems and Technology 2006. (pdf file)

Document Clustering using Nonnegative (Non-negative) Matrix Factorization, Farial Shahnaz, Michael Berry, Paul Pauca, and Robert Plemmons. Appeared in the Journal on Information Processing & Management, Vol. 42, pp. 373-386, 2006. (pdf file)

Nonnegative (Non-negative) Matrix Factorization and Applications, Moody Chu and Robert Plemmons. Appeared in IMAGE, Bulletin of the International Linear Algebra Society, Vol. 34, pp. 2-7, July 2005. (pdf file)

Computational Imaging Systems for Iris Recognition, Robert Plemmons, Michael Horvath, Emily Leonhardt, Paul Pauca, Sudhakar Prasad, Stephen Robinson, Harsha Setty, Todd Torgersen, Joseph van der Gracht, Edward Dowski, Ramkumar Narayanswamy, and Paulo E. X. Silveira. Appeared in Proc. SPIE Annual Meeting, Denver 2004. (pdf file)

High-Resolution Imaging Using Integrated Optical Systems, Sudhakar Prasad, Todd Torgersen, Paul Pauca, Robert Plemmons, and Joe van der Gracht. Appeared in the International Journal on Imaging Systems and Technology, Vol. 14, pp. 67-75, 2004. (pdf file)

Iris Recognition with Enhanced Depth-of-Field Image Aquisition, Joseph van der Gracht, Paul Pauca, Harsha Setty, Ramkumar Narayanswamy, Robert Plemmons, Sudhakar Prasad, and Todd Torgersen . Proc. SPIE Conference on Defense and Homeland Security, Orlando, April 2004. (pdf file)

Unmixing Spectral Data for Space Objects using Independent Component Analysis and Nonnegative ((Non-negative) Matrix Factorization, Paul Pauca, Robert Plemmons, Maile Giffin, Kris Hamada. Appeared in the Proc. Amos Technical Conf., Maui, 2004. (pdf file)

Text Mining using Nonnegative (Non-negative) Matrix Factorizations, Paul Pauca, Farial Shahnaz, Michael Berry and Robert Plemmons. Refereed paper. Appeared in the Proc. SIAM Inter. Conf. on Data Mining, Orlando, April 2004 . (pdf file)

An Integrated Optical-Digital Approach for Improved Image Restoration, Paul Pauca, Robert Plemmons, Sudhakar Prasad, Todd Torgersen, Joe van der Gracht and Curt Vogel. Appeared in the Proceedings AMOS Technical Conference, Maui, HI, September 2003. (pdf file)

On Reduced Rank Nonnegative (Non-negative) Matrix Factorizations for Symmetric Matrices, M. Catral, Lixing Han, Michael Neumann and Robert Plemmons. Appeared in Lin. Alg. and Applications, Vol.393, pp. 107-127, 2004.

Semi-Conjugate Direction Methods for Nonsymmetric Systems, J.Y. Yuan, G.H. Golub, R.J. Plemmons, and W.A.G. Cecilo. Appeared in BIT Numerical Mathematics, 2004.

Optimality, Computation, and Interpretations of Nonnegative Matrix Factorizations, Moody Chu, Fasma Diele, Robert Plemmons, and Stefania Ragni. October 2004. (pdf file)

Integrated Optical-Digital Approaches for Enhancing Image Restoration and Focus Invariance, Paul Pauca, Robert Plemmons, Sudhakar Prasad and Todd Torgersen. Proc. SPIE Annual Conf., July 2003. (pdf file)

Engineering the Pupil Phase for Image Quality, Sudhakar Prasad, Todd Torgersen, Paul Pauca, Robert Plemmons, and Joe van der Gracht. Proc. AeroSense Conference on Technologies and Systems for Defense and Security, Orlando, April 2003.

Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex Medium Response, Zhiping Mu, Robert Plemmons, and Pete Santago. International Journal on Imaging Systems and Technology 2006. (pdf file)

Regularized, In Toto, 3D Iterative Restoration of Tomosynthetic Images, Timothy Persons, Paul Hemler, Robert Plemmons and Dan Bourland. Technical Rept., 2002.

Iterative Restoration of Wavefront Coded Imagery for Focus Invariance, Joe van der Gracht, James Nagy, Paul Pauca and Robert Plemmons. Proc. ICIS Conference, Optical Soc. Amer. 2002.

Real-Valued, Low Rank Circulant Approximation, Moody Chu and Robert Plemmons. SIAM J. on Matrix Analysis, 2002.

Regularization Methods for Image Restoration Based on Autocorrelation Functions, Zhiping Mu and Robert Plemmons. In Proc. Annual SPIE Meeting, San Diego, 2000.

Exploiting Toeplitz Structure in Atmospheric Image Reconstruction, William Cochran, Robert Plemmons and Todd Torgersen. In Numerical Analysis and Theory of Computation, 2000.

Some Computational Problems Arising in Adaptive Optics Imaging Systems, Robert Plemmons and Paul Pauca. In Computatienal and Applied Mathematics – Special Series: Numerical Analysis in the 20th Century, 2000.

Algorithms and Software for Atmospheric Image Reconstruction, William Cochran, Robert Plemmons and Todd Torgersen. Proceedings of the AMOS Technical Conference, Maui, HI, 1999.

Structured Low Rank Approximation, Moody Chu, Robert Funderlic, and Robert Plemmons. Linear Algebra and Its Applications, 2003.

A New Approach to Constrained Total Least Squares Image Restoration, Michael K. Ng, Robert Plemmons and Felipe Pimentel. Appeared in Lin. Alg. Applic., 2000.

Efficient Two-Parameter Hankel Transforms in Adaptive Optics System Evaluations, Paul Pauca, Brent Ellerbroek, Robert Plemmons, and Xiaobai Sun. Appeared in Lin. Alg. Applic., 2000.

Regularized Iterative Blind Deconvolution using Recursive Inverse Filtering, Michael Ng, Robert Plemmons and Sanzheng Qiao. In the IEEE Trans. on Image Proc., 2000.

A Mathematical Framework for the Linear Reconstructor Problem in Adaptive Optics, Moody Chu, Paul Pauca, Robert Plemmons, and Xiaobai Sun. Appeared in Lin. Alg. Applic., 2000.

Fast Algorithms for Phase Diversity-Based Blind Deconvolution, Curtis R. Vogel, Tony Chan, and Robert J. Plemmons. Appeared in SPIE Proc. Conference on Astronomical Imaging, Kona, HI., 1998. (pdf file)

Preconditioned Iterative Regularization for Ill-Posed Problems, Martin Hanke , James G. Nagy, and Robert J. Plemmons. An older paper that was published in 1993.

W. Cochran, R.J. Plemmons, T.C. Torgersen, Algorithms and software for atmospheric image re- construction, in: Proceedings of the AMOS Technical Conference, Maui, HI, USA, 1999.

N. Pitsianis, B. Ellerbroek, C.F. VanLoan, R.J. Plemmons, Jacobi-like method for a problem arising in adaptive-optics, in: F.T. Luk (Ed.), Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, SPIE, vol. 3461, 1998, pp. 296–307.

V.P. Pauca, B.L. Ellerbroek, N.P. Pitsianis, R.J. Plemmons, X. Sun, Performance modeling of adaptive optics imaging systems using fast Hankel transforms, in: F.T. Luk (Ed.), Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, SPIE, vol. 3461, 1998, pp. 339– 347.

M.K. Ng, R.J. Plemmons, S. Qiao, Regularized blind deconvolution using recursive inverse filter- ing, in: Proceedings of the HK97 Conference on Scientific Computation, Springer, Berlin, 1998, pp. 110–132. 12 Preface / Linear Algebra and its Applications 316 (2000) 1–12.

G.H. Golub, S.H. Lui, F.T. Luk, R.J. Plemmons (Eds.), Scientific Computing, WSC’97, Proceedings of the Workshop Held in Hong Kong, 10–12 March, 1997, Springer, Berlin, 1998.

B. Ellerbroek, C.F. Van Loan, N. Pitsianis, R.J. Plemmons, Multiple control bandwidth computations in adaptive optics, in: F.T. Luk (Ed.), Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, SPIE, vol. 3461, 1998.

T.F. Chan, R.J. Plemmons, C.R. Vogel, Fast algorithms for phase diversity-based blind deconvolution, in: Proceedings of the Conference on Astronomical Imaging, Kona, HI, USA SPIE, 1998.

A. Berman, R.J. Plemmons, A note on simultaneously diagonalizable matrices, Math. Inequal. Appl. 1 (1998) 149–152.

R.J. Plemmons, Numerical linear algebra in optical imaging, in: Foundations of Computational Mathematics, Selected Papers of a Conference Held at IMPA in Rio de Janeiro, Brazil, January 1997, Springer, Berlin, 1997, pp. 362–367.

R.J. Plemmons, Iterative numerical methods for imaging through turbulence, in: Proceedings of the Conference on Iterative Solution Methods for Scientific Computation, Nijmegen, Netherlands, 1997.

J.G. Nagy, V.P. Pauca, R.J. Plemmons, T.C. Torgersen, Space-varying restoration of optical images, J. Opt. Soc. Amer. A 14 (1997) 3162–3174.

J.G. Nagy, V.P. Pauca, R.J. Plemmons, T.C. Torgersen, Degradation reduction in optics imagery using Toeplitz structure, Calcolo 33 (1997) 269–288.

R.J. Plemmons, Some applications of iterative deconvolution, South East Asia Bull. Math. 20 (1996) 23–32.

R.J. Plemmons, Inverse problems in atmospheric imaging, in: Proceedings of the Hellenic International Conference on Mathematics and Informatics, Athens, Greece, 1996, pp. 124–133.

R.J. Plemmons, Adaptive computations in optics, in: Proceedings of the Institute for Mathematical Sciences International Conference on Mathematics in Signal Processing, Warwick, UK, 1996.

M.K. Ng, R.J. Plemmons, LMS-Newton adaptive filtering using FFT, South East Asia Bull. Math. 20 (1996) 71–78.

M.K. Ng, R.J. Plemmons, LMS-Newton adaptive filtering by FFT-based conjugate gradient iterations, Electronic Trans. Numer. Anal. 4 (1996) 14–36.

M.K. Ng, R.J. Plemmons, Fast RLS adaptive filtering by FFT-based conjugate gradient iterations, SIAM J. Sci. Comput. 17 (1996) 920–941.

J.G. Nagy, R.J. Plemmons, T.C. Torgersen, Iterative image restoration using approximate inverse preconditioning, IEEE Trans. Image Process. 15 (1996) 1151–1162.

B. Ellerbroek, R.J. Plemmons, Leading edge methods in optical imaging, in: Success Stories in High Performance Computing, US Department of Defense Brochure, 1996.

R.H. Chan, M.K. Ng, R.J. Plemmons, Generalization of Strang’s preconditioner for Toeplitz least squares problems, Numer. Linear Algebra Appl. 3 (1996) 45–64.

M.K. Ng, R.J. Plemmons, Fast recursive least squares using the FFT, in: Proceedings of the Conference on Mathematics of Signal Processing, Warwick, UK, Oxford Press, Oxford, 1994, pp. 97–129.

J.G. Nagy, R.J. Plemmons, T.C. Torgersen, Fast restoration of atmospherically blurred images, in: F.T. Luk (Ed.), Advanced Signal Processing Algorithms, Architectures, and Implementations IV, SPIE, vol. 2295, 1994, pp. 542–553.

A. Hadjidimos, R.J. Plemmons, Optimal p-cyclic SOR, Numer. Math. 67 (1994) 475–490.

B. Ellerbroek, C. Van Loan, N. Pitsianis, R.J. Plemmons, Optimizing closed loop adaptive optics performance using multiple control bandwidths, J. Opt. Soc. Amer. 11 (1994) 2871–2886.

R.H. Chan, M.K. Ng, R.J. Plemmons, Preconditioners for atmospheric imaging, in: F.T. Luk (Ed.), Advanced Signal Processing Algorithms, Architectures, and Implementations IV, SPIE, vol. 2295, 1994, pp. 528–539.

R.H. Chan, J.G. Nagy, R.J. Plemmons, Displacement preconditioner for Toeplitz least squares iter- ations, Electronic Trans. Numer. Anal. 2 (1994) 44–65.

R.H. Chan, J.G. Nagy, R.J. Plemmons, Circulant preconditioned Toeplitz least squares iterations, SIAM J. Matrix Anal. Appl. 15 (1994) 80–97.

J.D. Brown, M.T. Chu, D.C. Ellison, R.J. Plemmons (Eds.), Proceedings of the Cornelius Lanczos International Centenary Conference, SIAM, Philadelphia, PA, USA, 1994.

A. Berman, R.J. Plemmons, Nonnegative Matrices in the Mathematical Sciences, SIAM, Philadelphia, PA, USA, 1994 (Revised edition of 1979 original).

R.J. Plemmons, FFT-based RLS in signal processing, in: Proceedings of the ICASSP- 93, Minneapolis, MN. USA, IEEE Press, New York, 1993.

J.G. Nagy, R.J. Plemmons, Some fast Toeplitz least squares algorithms, in: Proceedings of the 30th Allerton Conference on Communications, Control and Computing, Allerton, IL, USA, 1993, pp. 257–266.

C.D. Meyer, R.J. Plemmons (Eds.), Linear Algebra, Markov Chains, and Queueing Models, IMA, vol. 48, Springer, New York, NY, 1993.

M. Hanke, J.G. Nagy, R.J. Plemmons, Preconditioned iterative regularization for ill-posed problems, in: L. Reichel, A. Ruttan, R.S. Varga (Eds.), Numerical Linear Algebra, De Gruyter (Walter), Berlin, 1993, pp. 141–163.

A. Hadjidimos, R.J. Plemmons, Analysis of p-cyclic iterations for Markov chains, in: C. Meyer, R. Plemmons (Eds.), Linear Algebra, Markov Chains, and Queueing Models, IMA Volumes in Mathematics and Its Applications, vol. 48, Springer, Berlin, 1993, pp. 111–124.

R.H. Chan, J.G. Nagy, R.J. Plemmons, FFT-based preconditioners for Toeplitz-block least squares problems, SIAM J. Numer. Anal. 30 (1993) 1740–1768.

A.W. Bojanczyk, J.G. Nagy, R.J. Plemmons, Block RL Susingrow Householder reflections, Linear Algebra Appl. 188–189 (1993) 31–61.

D.J. Pierce, R.J. Plemmons, Tracking the condition number for RLS in signal processing, Math. Control Signals Systems 5 (1992) 23–39.

D.J. Pierce, R.J. Plemmons, Fast adaptive condition estimation, SIAM J. Matrix Anal. Appl. 13 (1992) 274–291.

J.G. Nagy, R.J. Plemmons, An inverse factorization algorithm for linear prediction, Linear Algebra Appl. 172 (1992) 169–195.

J.G. Nagy, R.J. Plemmons, A fast algorithm for linear prediction, in: H. Kimura, S. Kodama (Ed.), Mathematical Theory of Systems, Control, Networks and Signal Processing II, MTA Press, Tokyo, 1992, pp. 15–21.

A. Ghirinikar, S.T. Alexander, R.J. Plemmons, A parallel implementation of the inverse QR adaptive filter, Comput. Electric. Engrg. 18 (1992) 291–300.

R.H. Chan, J.G. Nagy, R.J. Plemmons, Block circulant preconditioners for 2-D deconvolution problems, in: F.T. Luk (Ed.), Proceedings of the SPIE Symposium on Advanced Signal Processing Algorithms, Architectures and Implementations, SPIE, vol. 1770, 1992, pp. 60–71.

J.G. Nagy, R.J. Plemmons, Some fast Toeplitz least squares algorithms, in: F.T. Luk (Ed.), Proceedings of the SPIE Symposium on Advanced Signal Processing Algorithms, Architectures, SPIE, vol. 1566, 1991, pp. 35–46.

K. Kontovasilis, R.J. Plemmons, W.J. Stewart, Block cyclic SOR for Markov chains with p-cyclic infinitesimal generator, Linear Algebra Appl. 154–156 (1991) 145–223.

C. Henkel, R.J. Plemmons, Recursive least squares on a hypercube multiprocessor using the covariance factor, SIAM J. Sci. Statist. Comput. 12 (1991) 95–106.

C.S. Henkel, R.J. Plemmons, Parallel recursive least squares on a hypercube multiprocessor, in: Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms, NATO ASI Series, volume Ser. F 70, 1991, pp. 571–577.

R. Ferng, G.H. Golub, R.J. Plemmons, Adaptive Lanczos methods for recursive condition estimation, Numer. Algorithms 1 (1991) 1–19.

R.J. Plemmons, R. White, Substructuring methods for computing the nullspace of equilibrium matrices, SIAM J. Matrix Anal. Appl. 11 (1990) 1–22.

R.J. Plemmons, Recursive least squares computations, in Proceedings of the International Symposium on MTNS-89, Signal Processing and Numerical Methods, vol. 3, Amsterdam, Birkhauser, Basel, 1990, pp. 495–502.

D.J. Pierce, A. Hadjidimos, R.J. Plemmons, Optimality relationships for cyclic SOR, Numer. Math. 56 (1990) 635–643.

D. James, R.J. Plemmons, An iterative substructuring algorithm for equilibrium equations, Numer. Math. 57 (1990) 625–633.

K. Gallivan, A. Sameh, R.J. Plemmons, M.T. Heath, E. Ng, B. Peyton, J. Ortega, C. Romine, R. Voigt, Parallel Algorithms for Matrix Computations, SIAM, Philadelphia, PA, USA, 1990.

K. Gallivan, R.J. Plemmons, A. Sameh, Parallel algorithms for dense linear algebra computations, SIAM Rev. 32 (1990) 54–135.

D. Agrawal, S. Kim, R.J. Plemmons, Least squares multiple updating algorithms on a hypercube, Internat. J. Parallel Process. 8 (1990) 80–88.

R.J. Plemmons, S.J. Wright, An efficient parallel scheme for minimizing a sum of Euclidean norms, Linear Algebra Appl. 121 (1989) 71–85.

R.J. Plemmons, Least squares computations for Geodetic and related problems, in: R. Williamson (Ed.), High Speed Computing, University of Illinois Press, Champaign, IL, USA, 1989, pp. 198–200.

C.T. Pan, R.J. Plemmons, Parallel least squares modifications with inverse factorizations: parallel implications, J. Comput. Appl. Math. 34 (1989) 109–127.

G.H. Golub, R.J. Plemmons, A. Sameh, Parallel block schemes for large-scale least squares computations, in: R. Williamson (Ed.), High Speed Computing, University of Illinois Press, Champaign, IL, USA, 1989, pp. 171–179.

D.J. Pierce, R.J. Plemmons, A two-level preconditioned conjugate gradient scheme, in: Proceedings of the Conference on Linear Algebra in Signals, Systems and Control, SIAM, Philadelphia, PA, USA, 1988, pp. 170–185.

C. Henkel, R.J. Plemmons, Recursive least squares computations on the hypercube multiprocessor, in: Proceedings of the NATO Workshop on Parallel Algorithms, Linear Algebra and Signal Processing, Brussels, Belgium, 1988.

M.T. Heath, C. Henkel, R.J. Plemmons, Cholesky downdating on a hypercube, in: G. Fox (Ed.), Hypercube Concurrent Computers and Applications. Vol. II. Applications, ACM Press, New York, 1988, pp. 1592–1598.

B. Datta, C.R. Johnson, M.A. Kaashoek, R.J. Plemmons, E.D. Sontag (Eds.), Linear Algebra in Signals, Systems and Control, SIAM, Philadelphia, PA, USA, 1988.

J. Barlow, N. Nichols, R.J. Plemmons, Iterative methods for equality constrained least squares problems, SIAM J. Sci. Statist. Comput. 9 (1988) 892–906.

S.T. Alexander, C.T. Pan, R.J. Plemmons, Analysis of a recursive least-squares hyperbolic rotation algorithm for signal processing, Linear Algebra Appl. 98 (1988) 3–40.

R.J. Plemmons, Parallel multisplitting iterative methods, in: F. Uhlig, R. Grone (Eds.), Current Trends in Matrix Theory, 1987, pp. 251–253.

R.J. Plemmons, Least squares computations for Geodetic and related problems, in: Proceedings of the Workshop on Scientific Applications and Algebraic Design for High Speed Computing, Urbana, IL, USA, 1987.

M. Neumann, R.J. Plemmons, Convergence of parallel multisplitting iterative methods, Linear Algebra Appl. 88 & 89 (1987) 559–573.

G.H. Golub, R.J. Plemmons, A. Sameh, Parallel block schemes for large-scale least squares computations, in: Proceedings of the Workshop on Scientific Applications and Algebraic Design for High Speed Computing, Urbana, IL, USA, 1987.

M.W. Berry, R.J. Plemmons, Algorithms and experiments for structural mechanics on high performance architectures, Comp. Methods Appl. Mech. Engrg. 64 (1987) 487–507.

S.T. Alexander, C.T. Pan, R.J. Plemmons, Numerical properties of a hyperbolic rotation scheme for windowed RLS filtering. in: Proceedings of the IEEE Conference on Acoustics, Speech and Signal Processing, vol. 1, Dallas, TX, USA, 1987, pp. 423–426.

R.J. Plemmons, A parallel block iterative scheme applied to computations in structural analysis, SIAM J. Algebraic Discrete Methods 7 (1986) 337–347.

R. Funderlic, R.J. Plemmons, Updating LU factorizations for computing stationary distributions, SIAM J. Algebraic Discrete Methods 7 (1986) 30–42.

J. Barlow, N. Nichols, R.J. Plemmons, A conjugate gradient method for equality constrained least squares, in: Proceedings of the Conference on Advanced Algorithms and Architectures for Signal Processing, SPIE, vol. 696, 1986, pp. 23–30.

G. Barker, R.J. Plemmons, Convergent iterations for computing stationary distributions of Markov chains, SIAM J. Algebraic Discrete Methods 7 (1986) 390–398.

T. Markham, M. Neumann, R.J. Plemmons, Convergence of a direct-iterative method for large-scale least squares problems, Linear Algebra Appl. 69 (1985) 155–167.

M.W. Berry, R.J. Plemmons, Parallel schemes for finite element structural analysis on the HEP multiprocessor, in: Proceedings of the Workshop on the Denelcor HEP, Norman, OK, USA, 1985, pp. 157–180.

M.W. Berry, R.J. Plemmons, Computing a banded basis of the null space on the Denelcor HEP multiprocessor, in: Proceedings of the AMS/SIAM Conference on the Role of Linear Algebra in Sys- tems Theory, Bowdoin, ME, USA, Contemporary Mathematics, vol. 47, American Mathematical Society, Providence, RI, 1985, pp. 7–23.

M.W. Berry, M.T. Heath, I. Kaneko, M. Lawo, R.J. Plemmons, R.C. Ward, An algorithm to compute a sparse basis of the null-space, Numer. Math. 47 (1985) 483–504.

M. Neumann, R.J. Plemmons, Backward error analysis for linear systems associated with inverses of H-matrices, BIT 24 (1984) 102–112.

I. Kaneko, R.J. Plemmons, Minimum norm solutions to linear elastic analysis problems, Internat. J. Numer. Methods Engrg. 20 (1984) 983–998.

M.T. Heath, R.J. Plemmons, R.C. Ward, Sparse orthogonal schemes for structural optimization using the force method, SIAM J. Sci. Statist. Comput. 5 (1984) 514–532.

W. Harrod, R.J. Plemmons, Comparison of some direct methods for computing stationary distributions of Markov chains, SIAM J. Sci. Statist. Comput. 5 (1984) 453–469.

R. Funderlic, R.J. Plemmons, A combined direct-iterative method for certain M-matrix linear systems, SIAM J. Algebraic Discrete Methods 5 (1984) 33–42.

R. Brualdi, D. Carlson, B. Datta, C. Johnson, R.J. Plemmons (Eds.), Linear Algebra and Its Role in Systems Theory, Contemporary Mathematics, vol. 47, American Mathematical Society, Providence, RI, 1984.

M.W. Berry, M.T. Heath, R.J. Plemmons, R.C. Ward, Comparison of some orthogonal schemes for structural optimization, in: Proceedings of the Army Conference on Applied Mathematics and Computing, Washington DC, USA, 1984, pp. 477–485.

G.P. Barker, R.J. Plemmons, Convergence of Gauss–Seidel iterations for computing stationary dis- tributions of Markov chains, in: Proceedings of the Interernational Conference on Linear Algebra and Applications, Vitoria, Spain, 1984, pp. 99–116.

R. Funderlic, M. Neumann, R.J. Plemmons, LU decompositions of generalized diagonally dominant matrices, Numer. Math. 40 (1982) 57–69.

D. Hume, J. Litzey, R.J. Plemmons, Software for ordering sparse problems prior to Givens reduc- tion, in: Proceedings of the Army Conference on Numerical Analysis and Computers, Huntsville, AL, USA, 1981, pp. 267–282.

A. George, M.T. Heath, R.J. Plemmons, Solution of large-scale least squares problems using auxiliary storage, SIAM J. Sci. Statist. Comput. 2 (1981) 416–429.

A. George, G.H. Golub, M.T. Heath, R.J. Plemmons, Least squares adjustment of large-scale Geodetic networks by sparse orthogonal decomposition, in: Proceedings of the International Symposium on Geodetic Networks, Munich, Germany, 1981, pp. 432–453.

R. Funderlic, R.J. Plemmons, LU decomposition of M-matrices by elimination without pivoting, Linear Algebra Appl. 41 (1981) 99–110.

A. Berman, B. Parlett, R.J. Plemmons, Diagonal scaling to an orthogonal matrix, SIAM J. Algebraic Discrete Methods 2 (1981) 57–65.

M. Neumann, R.J. Plemmons, M-matrix chacterizations. II. General M-matrices, Linear and Multilinear Algebra 9 (1980) 211–225.

G.H. Golub, R.J. Plemmons, Sparse least squares problems, in: Computing Methods in Applied Science and Engineering, Versailles, France, 1980, pp. 489–496.

G.H. Golub, R.J. Plemmons, Large-scale least squares adjustment in Geodesy by dissection and orthogonal decomposition, Linear Algebra Appl. 34 (1980) 3–28.

Å. Björck, R.J. Plemmons, H. Schneider (Eds.), Large Scale Matrix Computations, North-Holland, New York, 1980.

R.J. Plemmons, Adjustment by least squares in Geodesy using block iterative methods for sparse matrices, in: Proceedings of the Army Conference on Numerical Analysis and Computers, White Sands, NM, USA, 1979, pp. 151–186.

J. Ortega, R.J. Plemmons, Extensions of the Ostrowski–Reich theorem for SOR iterations, Linear Algebra Appl. 28 (1979) 177–191.

M.D. Gunzburger, R.J. Plemmons, Energy conserving norms for hyperbolic systems of partial differential equations, Math. Comp. 33 (1979) 1–10.

A. Berman, R.J. Plemmons, Nonnegative Matrices in the Mathematical Sciences, Academic Press, New York, 1979.

A. Berman, R.J. Plemmons, Generalized inverse-positivity and splittings of M-matrices, Linear Algebra Appl. 23 (1979) 21–35.

M. Neumann, R.J. Plemmons, Convergent nonnegative matrices and iterative methods for consistent linear systems, Numer. Math. 31 (1978) 265–279.

G.P. Barker, A. Berman, R.J. Plemmons, Positive diagonal solutions to the Lyapunov equation, Linear and Multilinear Algebra 5 (1978) 249–256.

R.J. Plemmons, M-matrix chacterizations. I. Nonsingular M-matrices, Linear Algebra Appl. 18 (1977) 175–188.

C.D. Meyer, R.J. Plemmons, Convergent powers of a matrix with applications to iterative methods for singular linear systems, SIAM J. Numer. Anal. 14 (1977) 699–705.

R.J. Plemmons, Regular splittings and the discrete Neumann problem, Numer. Math. 25 (1976) 153–161.

R.J. Plemmons, M-matrices leading to semi-convergent splittings, Linear Algebra Appl. 15 (1976) 243–252.

D. Hartfiel, C. Maxson, R.J. Plemmons, An note on Green’s relations on the matrix semigroup Nn, Proc. Amer. Math. Soc. 60 (1976) 11–15.

R. Cline, R.J. Plemmons, l2 solutions to underdetermined linear systems, SIAM Rev. 18 (1976) 92–106.

A. Berman, R.J. Plemmons, Eight types of matrix monotonicity, Linear Algebra Appl. 13 (1976) 115–123.

R.J. Plemmons, Note on a splitting approach to ill-conditioned least squares problems, Czechoslovak J. Math. 25 (1975) 531–535.

W.J. Kammerer, R.J. Plemmons, Direct iterative methods for least squares solutions to singular operator equations, J. Math. Anal. Appl. 49 (1975) 512–526.

R.J. Plemmons, Linear least squares using elimination and modified Gram–Schmidt, J. Assoc. Comput. Mach. 21 (1974) 581–585.

R.J. Plemmons, Direct iterative methods for linear systems using weak splittings, in: Proceedings of the Liblice II Conference on Numerical Analysis, Prague, Czechoslovakia, Acta Univ. Car., vol. 15, 1974, pp. 117–120.

R. Cline, R.J. Plemmons, G. Worm, Generalized inverses of certain Toeplitz matrices, Linear Algebra Appl. 8 (1974) 25–33.

A. Berman, R.J. Plemmons, Matrix group monotonicity, Proc. Amer. Math. Soc. 46 (1974) 355–359.

A. Berman, R.J. Plemmons, Inverses of nonnegative matrices, Linear and Multilinear Algebra 2 (1974) 161–172.

A. Berman, R.J. Plemmons, Cones and iterative methods for best least squares solutions of linear systems, SIAM J. Numer. Anal. 11 (1974) 145–154.

R.J. Plemmons, R.E. Cline, Erratum to “The generalized inverse of a nonnegative matrix”, Proc. Amer. Math. Soc. 39 (1973) 651.

R.J. Plemmons, Regular nonnegative matrices, Proc. Amer. Math. Soc. 39 (1973) 26–32.

J.S. Montague, R.J. Plemmons, Doubly stochastic matrix equations, Israel J. Math. 15 (1973) 216–229.

J. Wall, R.J. Plemmons, Spectral inverses of stochastic matrices, SIAM J. Appl. Math. 22 (1972) 22–26.

R.J. Plemmons, Monotonicity and iterative approximations involving rectangular matrices, Math. Comp. 26 (1972) 853–858.

R.J. Plemmons, Graphs and nonnegative matrices, Linear Algebra Appl. 5 (1972) 283–292.

J.S. Montague, R.J. Plemmons, Convex matrix equations, Bull. Amer. Math. Soc. 78 (1972) 965–968.

R. Cline, R.J. Plemmons, The generalized inverse of a nonnegative matrix, Proc. Amer. Math. Soc. 31 (1972) 46–50.

A. Berman, R.J. Plemmons, Monotonicity and the generalized inverse, SIAM J. Appl. Math. 22 (1972) 155–161.

R.J. Plemmons, M.T. West, On the semigroup of binary relations, Pacific J. Math. 35 (1971) 743–753.

R.J. Plemmons, Generalized inverses of Boolean relation matrices, SIAM J. Appl. Math. 20 (1971) 426–433.

R.J. Plemmons, R. Yoshida, Generating polynomials for finite semigroups, Math. Nachr. 47 (1970) 69–75.

R.J. Plemmons, B. Schein, Groups of binary relations, Semigroup Forum 1 (1970) 267–271.

R.J. Plemmons, On a conjecture concerning semigroup homomorphisms, Canad. J. Math.22 (1970) 641–644.

R.J. Plemmons, Graphs associated with a group, Proc. Amer. Math. Soc. 25 (1970) 273–275.

R.J. Plemmons, Construction and analysis of non-equivalent finite semigroups, and Cayley tables for all semigroups of orders at most 6, in: Proceedings of the Conference on Computational Problems in Algebra, Oxford, UK, Pergamon Press, Oxford, 1969, pp. 223–228.

J.S. Montague, R.J. Plemmons, Maximal subgroups of the semigroup of relations, J. Algebra 13 (1969) 575–587.

R.J. Plemmons, There are 15 973 semigroups of order 6, Math. Algebra 2 (1967) 2–17.

R.J. Plemmons, On computing non-equivalent finite algebraic systems, Math. Algebra 2 (1967) 80–84.

R.J. Plemmons, Maximal ideals in the direct product of two semigroups, Czechoslovak J. Math. 17 (1967) 257–260.

R.J. Plemmons, T. Tamura, Semigroups with a maximal homomorphic image having zero, Proc. Japan Acad. 41 (1965) 681–685.