DocumentCode
2934984
Title
A new method for signal sparse decomposition
Author
Liu, Danhua ; Shi, Guangming ; Gao, Dahua
Author_Institution
Xidian Univ., Xian
fYear
2007
fDate
Nov. 28 2007-Dec. 1 2007
Firstpage
750
Lastpage
753
Abstract
Increasing attention has been paid to the signal sparse representation based on overcomplete dictionaries in the fields of signal processing. The sparsity degree of decomposed signal is directly related with the dictionary chosen, and the computation speed depends on the sparse decomposition algorithm and the scale of dictionary. Almost all sparse decomposition algorithms available suffer from enormous computational complexity, which severely affects the practicability of these algorithms and limits the development of sparse representation upon an overcomplete dictionary. This paper presents a new method for decomposing a signal upon overcomplete dictionary. This method first constructs a special concatenate dictionary with several orthogonal bases and presents a iterative group matching search algorithm. The experiments results show that our algorithm can reduce the computation burden greatly and is more efficient than MP. This paper also proposes a method to determine a near optimal value of the total number of coefficients.
Keywords
iterative methods; search problems; signal processing; dictionary scale; iterative group matching search algorithm; overcomplete dictionary; signal processing; signal sparse decomposition; Computational complexity; Dictionaries; Feature extraction; Iterative algorithms; Iterative methods; Matching pursuit algorithms; Noise reduction; Signal analysis; Signal processing; Signal processing algorithms; iteration; overcomplete dictionary; sparse coefficients;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Signal Processing and Communication Systems, 2007. ISPACS 2007. International Symposium on
Conference_Location
Xiamen
Print_ISBN
978-1-4244-1447-5
Electronic_ISBN
978-1-4244-1447-5
Type
conf
DOI
10.1109/ISPACS.2007.4445996
Filename
4445996
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