Title: Sparse approximations with a high resolution greedy algorithm
Abstract:Signal decomposition with an overcomplete dictionary is nonunique. Computation of the best approximation is known to be NP-hard problem. The matching pursuit (MP) algorithm is a popular iterative gree...Signal decomposition with an overcomplete dictionary is nonunique. Computation of the best approximation is known to be NP-hard problem. The matching pursuit (MP) algorithm is a popular iterative greedy algorithm that finds a sub-optimal approximation, by picking at each iteration the vector that best correlates with the present residual. Choosing approximation vectors by optimizing a correlation inner product can produce a loss of time and frequency resolution. We propose a modified MP, based on a post processing step applied on the resulting MP approximation, using the backward greedy algorithm, to achieve higher resolution than the original MP.Read More
Publication Year: 2005
Publication Date: 2005-03-31
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 2
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