Skip to main content

Algorithms for Blind Components Separation and Extraction from the Time-Frequency Distribution of Their Mixture

Abstract

We propose novel algorithms to select and extract separately all the components, using the time-frequency distribution (TFD), of a given multicomponent frequency-modulated (FM) signal. These algorithms do not use any a priori information about the various components. However, their performances highly depend on the cross-terms suppression ability and high time-frequency resolution of the considered TFD. To illustrate the usefulness of the proposed algorithms, we applied them for the estimation of the instantaneous frequency coefficients of a multicomponent signal and the results are compared with those of the higher-order ambiguity function (HAF) algorithm. Monte Carlo simulation results show the superiority of the proposed algorithms over the HAF.

Author information

Affiliations

Authors

Corresponding author

Correspondence to B. Barkat.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Barkat, B., Abed-Meraim, K. Algorithms for Blind Components Separation and Extraction from the Time-Frequency Distribution of Their Mixture. EURASIP J. Adv. Signal Process. 2004, 978487 (2004). https://doi.org/10.1155/S1110865704404193

Download citation

Keywords and phrases

  • time-frequency signal analysis
  • components separation
  • polynomial phase signals
  • instantaneous frequency estimation