回溯式在线EASI盲源分离算法

Retrospective on-line EASI blind source separation algorithm

  • 摘要: 针对现有的在线盲源分离算法在时变混合矩阵突变后初始阶段分离精度低的问题,提出一种改进的在线盲分离算法。该算法通过检测误差函数的变化来确定时变混合矩阵的突变点,并利用突变前收敛较好的分离矩阵对之前的观测数据进行回溯分离。仿真结果表明,对于具有间歇式突变的时变混合环境的场景,相较于传统在线盲分离算法,提出的回溯式在线EASI盲源分离算法能提高分离初始阶段的分离精度,有效地跟踪混合矩阵的突变。

     

    Abstract: Aiming at the problem of low separation accuracy at the initial stages after an abrupt change of the time-varying mixing matrix, this paper proposed an improved on-line blind separation algorithm. The mutation point of the time-varying mixing matrix was determined by detecting the changes of the error function, and then used better converged separation matrix to separate the observed data retrospectively. Simulation results show that with the mixing scene of intermittent mutation, the proposed retrospective on-line EASI blind source separation algorithm can improve the separation accuracy at the initial stages and effectively track the mutation of the mixing matrix.

     

/

返回文章
返回