• DocumentCode
    311323
  • Title

    Wavelet-based transformations for nonlinear signal processing

  • Author

    Nowak, Robert D. ; Baraniuk, Richard G.

  • Author_Institution
    Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
  • Volume
    3
  • fYear
    1997
  • fDate
    21-24 Apr 1997
  • Firstpage
    2385
  • Abstract
    Nonlinearities are often encountered in the analysis and processing of real-world signals. This paper develops new transformations for nonlinear signal processing. The theory of tensor norms is employed to show that wavelets provide an optimal basis for the new transformations. The results are applied to Volterra kernel identification
  • Keywords
    Volterra series; filtering theory; signal processing; tensors; wavelet transforms; Volterra filter; Volterra kernel identification; nonlinear signal processing; nonlinearities; signal analysis; tensor norms; wavelet based transformations; Couplings; Filtering; Harmonic distortion; Kernel; Machinery; Signal analysis; Signal processing; Speech processing; Tensile stress; Wavelet domain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
  • Conference_Location
    Munich
  • ISSN
    1520-6149
  • Print_ISBN
    0-8186-7919-0
  • Type

    conf

  • DOI
    10.1109/ICASSP.1997.599534
  • Filename
    599534
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=311323