TY - GEN
T1 - Sparse approximations with a high resolution greedy algorithm
AU - Salomon, Benjamin G.
AU - Ur, Hanoch
PY - 2004
Y1 - 2004
N2 - 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 backward greedy algorithm, to achieve higher resolution than the original MP.
AB - 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 backward greedy algorithm, to achieve higher resolution than the original MP.
UR - http://www.scopus.com/inward/record.url?scp=27644583299&partnerID=8YFLogxK
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AN - SCOPUS:27644583299
SN - 0780387155
T3 - 11th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2004
SP - 330
EP - 333
BT - 11th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2004
T2 - 11th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2004
Y2 - 13 December 2004 through 15 December 2004
ER -