Using Hankel Structured Low-Rank Approximation for Sparse Signal Recovery

Latent Variable Analysis and Signal Separation - Lecture Notes in Computer Science ◽

10.1007/978-3-319-93764-9_44 ◽

2018 ◽

pp. 479-487

Author(s):

Ivan Markovsky ◽

Pier Luigi Dragotti

Keyword(s):

Low Rank ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Low Rank Approximation ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text

Global Optimization Challenges in Structured Low Rank Approximation

Lecture Notes in Computer Science - Learning and Intelligent Optimization ◽

10.1007/978-3-319-69404-7_26 ◽

2017 ◽

pp. 326-330

Author(s):

Jonathan Gillard ◽

Anatoly Zhigljavsky

Keyword(s):

Global Optimization ◽

Low Rank ◽

Low Rank Approximation ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text

Software package for mosaic-Hankel structured low-rank approximation

2019 IEEE 58th Conference on Decision and Control (CDC) ◽

10.1109/cdc40024.2019.9028867 ◽

2019 ◽

Author(s):

Konstantin Usevich ◽

Ivan Markovsky

Keyword(s):

Software Package ◽

Low Rank ◽

Low Rank Approximation ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text

Sparse Signal Recovery from Fixed Low-Rank Subspace via Compressive Measurement

10.3390/a6040871 ◽

2013 ◽

Vol 6 (4) ◽

pp. 871-882 ◽

Author(s):

Jun He ◽

Ming-Wei Gao ◽

Lei Zhang ◽

Hao Wu

Keyword(s):

Low Rank ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery

Download Full-text

On a fixed-point algorithm for structured low-rank approximation and estimation of half-life parameters

2016 24th European Signal Processing Conference (EUSIPCO) ◽

10.1109/eusipco.2016.7760263 ◽

2016 ◽

Author(s):

Fredrik Andersson ◽

Marcus Carlsson ◽

Herwig Wendt

Keyword(s):

Fixed Point ◽

Half Life ◽

Low Rank ◽

Low Rank Approximation ◽

Fixed Point Algorithm ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text

A Quadratically Convergent Algorithm for Structured Low-Rank Approximation

Foundations of Computational Mathematics ◽

10.1007/s10208-015-9256-x ◽

2015 ◽

Vol 16 (2) ◽

pp. 457-492 ◽

Author(s):

Éric Schost ◽

Pierre-Jean Spaenlehauer

Keyword(s):

Low Rank ◽

Low Rank Approximation ◽

Rank Approximation ◽

Convergent Algorithm ◽

Structured Low Rank Approximation

Download Full-text

A class of multilevel structured low-rank approximation arising in material processing

International Journal of Computer Mathematics ◽

10.1080/00207160.2017.1285020 ◽

2017 ◽

Vol 95 (2) ◽

pp. 329-340 ◽

Author(s):

Jianchao Bai ◽

Jicheng Li ◽

Junkai Deng

Keyword(s):

Material Processing ◽

Low Rank ◽

Low Rank Approximation ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text

Analysis of Structured Low Rank Approximation as an Optimization Problem

Informatica ◽

10.15388/informatica.2011.338 ◽

2011 ◽

Vol 22 (4) ◽

pp. 489-505 ◽

Author(s):

Jonathan Gillard ◽

Anatoly Zhigljavsky

Keyword(s):

Optimization Problem ◽

Low Rank ◽

Low Rank Approximation ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text

Low-rank and joint-sparse signal recovery using sparse Bayesian learning in a WBAN

Multidimensional Systems and Signal Processing ◽

10.1007/s11045-020-00743-y ◽

2020 ◽

Author(s):

Yan-Bin Zhang ◽

Long-Ting Huang ◽

Yang-Qing Li ◽

Ke-Sen He ◽

Kai Zhang ◽

...

Keyword(s):

Bayesian Learning ◽

Low Rank ◽

Sparse Signal ◽

Sparse Signal Recovery ◽

Signal Recovery ◽

Sparse Bayesian Learning

Download Full-text

STRUCTURED LOW RANK APPROXIMATION

Inverse Eigenvalue Problems ◽

10.1093/acprof:oso/9780198566649.003.0008 ◽

2005 ◽

pp. 246-338

Author(s):

Moody T. Chu ◽

Gene H. Golub

Keyword(s):

Low Rank ◽

Low Rank Approximation ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text

Recent progress on variable projection methods for structured low-rank approximation

Signal Processing ◽

10.1016/j.sigpro.2013.09.021 ◽

2014 ◽

Vol 96 ◽

pp. 406-419 ◽

Author(s):

Ivan Markovsky

Keyword(s):

Recent Progress ◽

Projection Methods ◽

Low Rank ◽

Low Rank Approximation ◽

Variable Projection ◽

Rank Approximation ◽

Structured Low Rank Approximation

Download Full-text