Low-complexity compressive sensing with downsampling
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- Low-complexity compressive sensing with downsampling
- Lee, Dongeun; Choi, Jaesik; Shin, Heonshik
- Compressive sensing; Downsampling; Low-complexity; Sparse random matrix; Sparse signal recovery
- Issue Date
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- IEICE ELECTRONICS EXPRESS, v.11, no.3, pp.1 - 6
- Compressive sensing (CS) with sparse random matrix for the random sensing basis reduces source coding complexity of sensing devices. We propose a downsampling scheme to this framework in order to further reduce the complexity and improve coding efficiency simultaneously. As a result, our scheme can deliver significant gains to a wide variety of resource-constrained sensors. Experimental results show that the computational complexity decreases by 99.95% compared to other CS framework with dense random measurements. Furthermore, bit-rate can be saved up to 46.29%, by which less bandwidth is consumed.
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