Title :
Hybrid greedy pursuit
Author :
Chatterjee, Saikat ; Sundman, Dennis ; Vehkapera, Mikko ; Skoglund, Mikael
Author_Institution :
Commun. Theor. Lab., KTH - R. Inst. of Technol., Stockholm, Sweden
fDate :
Aug. 29 2011-Sept. 2 2011
Abstract :
For constructing the support set of a sparse vector in the standard compressive sensing framework, we develop a hybrid greedy pursuit algorithm that combines the advantages of serial and parallel atom selection strategies. In an iterative framework, the hybrid algorithm uses a joint sparsity information extracted from the independent use of serial and parallel greedy pursuit algorithms. Through experimental evaluations, the hybrid algorithm is shown to provide a significant improvement for the support set recovery performance.
Keywords :
compressed sensing; greedy algorithms; iterative methods; compressive sensing; hybrid greedy pursuit algorithm; iterative framework; joint sparsity information extraction; parallel atom selection strategy; serial atom selection strategy; sparse vector; Joints; Matching pursuit algorithms; Measurement uncertainty; Noise measurement; Pursuit algorithms; Standards; Vectors;
Conference_Titel :
Signal Processing Conference, 2011 19th European
Conference_Location :
Barcelona