TY  - CHAP
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6349795&isnumber=6349703
KW  - K-SVD algorithm
KW  -  T-mindot
KW  -  clustering
KW  -  large datasets training
KW  -  representation errors
KW  -  signal processing
KW  -  sparse representations 
EP  - 5
PB  - IEEE
SP  - 1
ID  - eprints1528
Y1  - 2012///
SN  - 978-1-4673-1025-3
A1  - Rusu, Cristian
TI  - Fast design of efficient dictionaries for sparse representations
N2  - One of the central issues in the field of sparse representations is the design of overcomplete dictionaries with a fixed sparsity level from a given dataset. This article describes a fast and efficient procedure for the design of such dictionaries. The method implements the following ideas: a reduction technique is applied to the initial dataset to speed up the upcoming procedure; the actual training procedure runs a more sophisticated iterative expanding procedure based on K-SVD steps. Numerical experiments on image data show the effectiveness of the proposed design strategy.
T2  - IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2012
AV  - none
ER  -