IEICE Electronics Express
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Low-complexity compressive sensing with downsampling
Dongeun LeeJaesik ChoiHeonshik Shin
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Volume 11 (2014) Issue 3 Pages 20130947

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Abstract

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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© 2014 by The Institute of Electronics, Information and Communication Engineers
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