Using reed-muller sequences as deterministic compressed sensing matrices for image reconstruction

2010 ◽  
Author(s):  
Kangyu Ni ◽  
Somantika Datta ◽  
Prasun Mahanti ◽  
Svetlana Roudenko ◽  
Douglas Cochran
Keyword(s):  
Image Reconstruction ◽  
Compressed Sensing ◽  
Compressed Sensing Matrices ◽  
Sensing Matrices

Toeplitz-Structured Compressed Sensing Matrices

2007 ◽  
Author(s):  
Waheed U. Bajwa ◽  
Jarvis D. Haupt ◽  
Gil M. Raz ◽  
Stephen J. Wright ◽  
Robert D. Nowak
Keyword(s):  
Compressed Sensing ◽  
Compressed Sensing Matrices ◽  
Sensing Matrices

Construction of compressed sensing matrices for signal processing

2018 ◽  
Vol 77 (23) ◽  
pp. 30551-30574 ◽  
Author(s):  
Yingmo Jie ◽  
Cheng Guo ◽  
Mingchu Li ◽  
Bin Feng
Keyword(s):  
Signal Processing ◽  
Compressed Sensing ◽  
Compressed Sensing Matrices ◽  
Sensing Matrices

scholarly journals Deterministic Compressed Sensing Matrices From Sequences With Optimal Correlation

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 16704-16710 ◽  
Author(s):  
Zhi Gu ◽  
Zhengchun Zhou ◽  
Yang Yang ◽  
Avik Ranjan Adhikary ◽  
Xiaolun Cai
Keyword(s):  
Compressed Sensing ◽  
Compressed Sensing Matrices ◽  
Sensing Matrices

Constructions of compressed sensing matrices based on the subspaces of symplectic space over finite fields

2015 ◽  
Vol 15 (02) ◽  
pp. 1650025 ◽  
Author(s):  
You Gao ◽  
Xiaojuan Zhang
Keyword(s):  
Compressed Sensing ◽  
Finite Fields ◽  
Symplectic Geometry ◽  
Symplectic Space ◽  
The Matrix ◽  
Compressed Sensing Matrices ◽  
Sensing Matrices

The paper provides two constructions of compressed sensing matrices using the subspaces of symplectic space and singular symplectic space over finite fields. Then we compare the matrices constructed in this paper with the matrix constructed by DeVore, and compare the two matrices based on symplectic geometry and singular symplectic geometry over finite fields.

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