Title :
Constructing Test Instances for Basis Pursuit Denoising
Author_Institution :
Inst. for Anal. & Algebra, Tech. Univ. Braunschweig, Braunschweig, Germany
Abstract :
The number of available algorithms for the so-called Basis Pursuit Denoising problem (or the related LASSO-problem) is large and keeps growing. Similarly, the number of experiments to evaluate and compare these algorithms on different instances is growing. In this correspondence, we present a method to produce instances with exact solutions that is based on a simple observation, related to the so-called source condition from sparse regularization.
Keywords :
signal denoising; signal reconstruction; LASSO-problem; basis pursuit denoising problem; source condition; sparse regularization; Dynamic range; Inverse problems; Minimization; Noise; Noise reduction; Sparse matrices; Vectors; Basis Pursuit denoising; compressed sensing; optimization; optimization algorithms; signal processing algorithms; sparsity;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2012.2236322