• 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