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- Title
Sensing matrix based on Kasami codes for compressive sensing.
- Authors
Nouasria, Hamid; Et‐tolba, Mohamed
- Abstract
Compressive sensing (CS) aims at acquiring sparse or compressible signals at a sampling rate much lower than Nyquist frequency. It allows for the original signal to be reconstructed from a small number of measurements. This involves an appropriate design of the sensing matrix to ensure signal recovery while reducing the number of measurements. In this study, the authors propose an improved deterministic Kasami sensing matrix whose columns have an enhanced orthogonality property. They demonstrate that the proposed matrix is suitable for existing recovery algorithms. Moreover, it outperforms the most existing sensing matrices in terms of the rate of exact reconstruction. In addition, it is shown that the use of the new sensing matrix for CS reduces significantly the memory requirement and the computational complexity.
- Publication
IET Signal Processing (Wiley-Blackwell), 2018, Vol 12, Issue 8, p1064
- ISSN
1751-9675
- Publication type
Article
- DOI
10.1049/iet-spr.2017.0537