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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.

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Correspondence to B. Barkat.

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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

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  • DOI: https://doi.org/10.1155/S1110865704404193

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