SL0 Algorithm for Compressed Sensing
MATLAB Implementation of the SL0 Algorithm for Compressed Sensing
Smoothed L0 (SL0) Algorithm for Compressed Sensing
The SL0 algorithm is a novel sparse reconstruction technique in compressed sensing that approximates the L0-norm optimization problem using smooth functions like Gaussian functions, transforming NP-hard problems into smooth convex optimization problems. Based on our tests, SL0 demonstrates significantly higher computational efficiency compared to traditional algorithms like OMP and BP, while maintaining good accuracy, though it has slightly lower noise tolerance.
SL0 Algorithm Implementation for Sparse Signal Reconstruction
Implementation of the Smoothed L0 (SL0) Algorithm with Efficient Code Structure for Compressed Sensing Applications