Identification of Chirps with Continuous Wavelet Transform

  • René Carmona
  • Wen Liang Hwang
  • Bruno Torrésani
Part of the Lecture Notes in Statistics book series (LNS, volume 103)


Chirps are signals (or sums of signals) that may be characterized by a local (i.e. time-dependent) amplitude and a local frequency. Time-frequency representations such as wavelet representations are well adapted to the characterization problem of such chirps. Ridges in the modulus of the transform determine regions in the transform domain with a high concentration of energy, and are regarded as natural candidates for the characterization and the reconstruction of the original signal. A couple of algorithmic procedures for the estimation of ridges from the modulus of the (continuous) wavelet transform of one-dimensional signals are described, together with a new reconstruction procedure, using only information of the restriction of the wavelet transform to a sample of points from the ridge. This provides with a very efficient way to code the information contained in the signal.


Cost Function Instantaneous Frequency Continuous Wavelet Transform Noisy Signal Chirp Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York 1995

Authors and Affiliations

  • René Carmona
    • 1
  • Wen Liang Hwang
    • 1
  • Bruno Torrésani
    • 2
  1. 1.Department of MathematicsUniversity of California at IrvineIrvineUSA
  2. 2.CNRS-Luminy, Case 907CPTMarseille Cedex 09France

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