• DocumentCode
    387844
  • Title

    Periodicity estimation by hypothesis-directed search

  • Author

    Amuedo, John

  • Author_Institution
    M.I.T. Artificial Intelligence Laboratory, Cambridge, Mass.
  • Volume
    10
  • fYear
    1985
  • fDate
    31138
  • Firstpage
    395
  • Lastpage
    398
  • Abstract
    Some methods are described for estimating the fundamental periodicity of additively combined quasi-periodic signals. These methods operate from measurements of the instantaneous amplitudes and frequencies of important sinusoidal components of the input signal. The methods share a similar computational structure, in which each component is allowed to assert a number of hypotheses as to possible fundamental periodicities to which it is related. Hypotheses from different components are combined in such a way as to reinforce common periodicities shared by several components. The methods discussed seem well suited to signals whose fundamental frequencies may be high, and vary over a wide range.
  • Keywords
    Artificial intelligence; Frequency estimation; Frequency measurement; Humans; Laboratories; Multiple signal classification; Music; Signal analysis; Signal resolution; Speech analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '85.
  • Type

    conf

  • DOI
    10.1109/ICASSP.1985.1168414
  • Filename
    1168414