193 / 2019-12-30 07:56:00
Approximate Joint Diagonalization for ARMA Dependent Source Separation
Source Separation; Auto regressive moving average signal; Dependent sources; Approximate joint diagonalization
全文录用
Saliha Meziani / Ecole Militaire Polytechnique, Algeria
Adel Belouchrani / Ecole Nationale Polythechnique, Algiers, Algeria
Karim Abed-Meraim / University of Orleans & PRISME Lab., France
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.
重要日期
  • 会议日期

    06月08日

    2020

    06月11日

    2020

  • 01月12日 2020

    初稿截稿日期

  • 04月15日 2020

    提前注册日期

  • 12月31日 2020

    注册截止日期

主办单位
IEEE Signal Processing Society
承办单位
Zhejiang University
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询