DocumentCode :
2793068
Title :
Structured and incoherent parametric dictionary design
Author :
Yaghoobi, Mehrdad ; Daudet, Laurent ; Davies, Michael E.
Author_Institution :
Inst. for Digital Commun. (IDCom), Univ. of Edinburgh, Edinburgh, UK
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
5486
Lastpage :
5489
Abstract :
A new dictionary selection approach for sparse coding, called parametric dictionary design, has recently been introduced. The aim is to choose a dictionary from a class of admissible dictionaries which can be presented parametrically. The designed dictionary satisfies a constraint, here the incoherence property, which can help conventional sparse coding methods to find sparser solutions in average. In this paper, an extra constraint will be applied on the parametric dictionaries to find a structured dictionary. Various structures can be imposed on dictionaries to promote a correlation between the atoms. We intentionally choose a structure to implement the dictionary using a set of filter banks. This indeed helps to implement the dictionary-signal multiplications more efficiently. The price we pay for the extra structure is that the designed dictionary is not as incoherent as unstructured parametric designed dictionaries.
Keywords :
encoding; admissible dictionaries; conventional sparse coding; dictionary-signal multiplications; filter banks; incoherence property; parametric dictionary design; structured dictionary; Approximation algorithms; Dictionaries; Digital communication; FETs; Filter bank; Learning systems; Linear systems; Optimization methods; Signal generators; Sparse matrices; Dictionary Selection; Parametric Dictionary Design; Sparse Approximation; Structured Dictionary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5495207
Filename :
5495207
Link To Document :
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