Approximate Joint Diagonalization for ARMA Dependent Source Separation
ID:119 View Protection:ATTENDEE Updated Time:2020-08-05 10:17:28 Hits:361 Oral Presentation

Start Time:2020-06-08 15:00(Asia/Shanghai)

Duration:20min

Session:S Special Session » SS14Dependent Source Separation

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Abstract
In this paper, an Approximate Joint Diagonalization (AJD) approach is proposed to separate dependent source signals. The diagonal structure of the Auto Regressive Moving Average (ARMA) matrix coefficients moves the problem from Blind Source Separation (BSS) to AJD one. The identified matrix coefficients of the observed signal are jointly diagonalized to achieve the mixture matrix identification. Simulation results are provided to illustrate the effectiveness of the proposed approach.
Keywords
Source Separation; Auto regressive moving average signal; Dependent sources; Approximate joint diagonalization
Speaker
Saliha Meziani
Ecole Militaire Polytechnique, Algeria

Submission Author
Saliha Meziani Ecole Militaire Polytechnique, Algeria
Adel Belouchrani Ecole Nationale Polythechnique, Algiers, Algeria
Karim Abed-Meraim University of Orleans & PRISME Lab., France
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    Jun 08

    2020

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    Jun 11

    2020

  • Jan 12 2020

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  • Apr 15 2020

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