Title :
Recipes on hard thresholding methods
Author :
Kyrillidis, Anastasios ; Cevher, Volkan
Author_Institution :
Lab. for Inf. & Inference Syst., Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland
Abstract :
We present and analyze a new set of sparse recovery algorithms within the class of hard thresholding methods. We provide optimal strategies on how to set up these algorithms via basic “ingredients” for different configurations to achieve complexity vs. accuracy tradeoffs. Simulation results demonstrate notable performance improvements compared to state-of-the-art algorithms both in terms of data reconstruction and computational complexity.
Keywords :
computational complexity; signal reconstruction; computational complexity; data reconstruction; hard thresholding methods; sparse recovery algorithms; Complexity theory; Convergence; Manganese; Signal reconstruction; Silicon; Stability analysis; Vectors;
Conference_Titel :
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2011 4th IEEE International Workshop on
Conference_Location :
San Juan
Print_ISBN :
978-1-4577-2104-5
DOI :
10.1109/CAMSAP.2011.6136024