A novel parallel reconstruction approach based on a semi-tensor product (STP) is proposed. A low-dimensional random matrix where the dimensions are 1/4.
In large-scale applications of compressed sensing (CS), the time cost to reconstruct the original signal is too high. To accelerate the reconstruction and ...
In reference [16] , the authors used the semi-tensor product to construct a measurement matrix, which reduced the storage space required for the measurement ...
Numerical results show that the speed can be effectively improved (10×, or 100×, even 1000×) and the storage space of the matrix can also be remarkably reduced; ...
Jinming Wang , Zhenyu Xu, Zhangquan Wang, Sen Xu, Jun Jiang: Rapid compressed sensing reconstruction: A semi-tensor product approach.
Download 16 pages fulltext PDF article from 2020 journal: Rapid compressed sensing reconstruction: A semi-tensor product approach.
Rapid compressed sensing reconstruction: A semi-tensor product approach. J. Wang, Z. Xu, Z. Wang, S. Xu, and J. Jiang. Inf. Sci., (2020 ).
Aug 8, 2018 · Abstract: To reduce the storage space of random measurement matrix and improve the reconstruction efficiency for compressed sensing (CS),a new ...
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This paper proposes a regularized model for 1-bit compressed sensing that provides an approximate estimate of the underlying signal with upper bounds on ...
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Rapid compressed sensing reconstruction: A semi-tensor product approach. Published:2020-02 Issue: Volume:512 Page:693-707. ISSN:0020-0255. Container-title ...