1 research outputs found
Binary Compressive Sensing via Smoothed Gradient Descent
We present a Compressive Sensing algorithm for reconstructing binary signals
from its linear measurements. The proposed algorithm minimizes a non-convex
cost function expressed as a weighted sum of smoothed norms which
takes into account the binariness of signals. We show that for binary signals
the proposed algorithm outperforms other existing algorithms in recovery rate
while requiring a short run time