Modified Recovery Algorithms Using proposed algorithm for Compressive Sampling | ||
| Menoufia Journal of Electronic Engineering Research | ||
| Article 1, Volume 26, Issue 1, January 2017, Pages 1-20 PDF (557.53 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/mjeer.2017.63112 | ||
| Authors | ||
| Wafaa Shalaby; Waleed Saad; Mona Shokair; Moawad Dessouky | ||
| Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt | ||
| Abstract | ||
| Compressive sampling (CS) has been an effective research area which plays an efficient role in many applications such as cognitive radio, imaging, radar and many other applications. In CS only a small number of linear measurements are used for reconstruction of the signal. The significant condition for dealing with compressed sensing system is that the signal in the input must be sparse. Most signals in nature are sparse or can be transformed to sparse by using any transform domain. This paper modifies all the recovery algorithms by using the proposed complex to real transformation algorithm. Conversion from not sparse signal to sparse by using Fourier transform will produce complexity, where this complexity can be removed using complex to real transformation algorithm and then applying it on all recovery algorithms to enhance their performance. By using the proposed algorithm, the sparse signal will be recovered in minimum error and less time. Also, the signal to error ratio from the recovery process is increased. | ||
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