• DocumentCode
    336189
  • Title

    Symbolic signal processing

  • Author

    Johnson, Don H. ; Wang, Wei

  • Author_Institution
    Comput. & Inf. Technol. Inst., Rice Univ., Houston, TX, USA
  • Volume
    3
  • fYear
    1999
  • fDate
    15-19 Mar 1999
  • Firstpage
    1361
  • Abstract
    Symbolic signals are, in discrete-time, sequences of quantities that do not assume numeric values. In the most general case, these quantities have no mathematical structure other than that they are members of some set, but they can have a sequential structure. The authors show that processing such signals does not entail mapping them directly to the integers, which would impose more structure-ordering and arithmetic-than present in the data. The authors describe how linear estimation and prediction can be performed on symbolic sequences. They show how spectrograms can be computed from neural population responses and from DNA sequences
  • Keywords
    DNA; biological techniques; biology computing; molecular biophysics; neurophysiology; parameter estimation; prediction theory; sequences; signal processing; spectral analysis; DNA sequences; arithmetic; discrete-time sequences; linear estimation; molecular biology; neural population responses; ordering; sequential structure; set; spectrograms; symbolic sequences; symbolic signal processing; DNA computing; Data engineering; Geophysical signal processing; Geophysics computing; Information analysis; Information technology; Neurons; Sequences; Signal processing; Spectrogram;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
  • Conference_Location
    Phoenix, AZ
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-5041-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.1999.756233
  • Filename
    756233