中国邮电高校学报(英文) ›› 2017, Vol. 24 ›› Issue (3): 7-15.doi: 10.1016/S1005-8885(17)60206-1

• Artificial Intelligence • 上一篇    下一篇

Low-complexity single-channel blind source separation

张星,胡建浩   

  1. 电子科技大学
  • 收稿日期:2016-11-17 修回日期:2017-04-11 出版日期:2017-06-30 发布日期:2017-06-30
  • 通讯作者: 张星 E-mail:xingzh_57@163.com

Low-complexity single-channel blind source separation

  • Received:2016-11-17 Revised:2017-04-11 Online:2017-06-30 Published:2017-06-30
  • Contact: Xing Zhang E-mail:xingzh_57@163.com

摘要: For the time-frequency overlapped signals, a low-complexity single-channel blind source separation (SBSS) algorithm is proposed in this paper. The algorithm does not only introduce the Gibbs sampling theory to separate the mixed signals, but also adopts the orthogonal triangle decomposition-M (QRD-M) to reduce the computational complexity. According to analysis and simulation results, we demonstrate that the separation performance of the proposed algorithm is similar to that of the per-survivor processing (PSP) algorithm, while its computational complexity is sharply reduced.

关键词: single-channel, separation, Gibbs sampling, QRD-M

Abstract: For the time-frequency overlapped signals, a low-complexity single-channel blind source separation (SBSS) algorithm is proposed in this paper. The algorithm does not only introduce the Gibbs sampling theory to separate the mixed signals, but also adopts the orthogonal triangle decomposition-M (QRD-M) to reduce the computational complexity. According to analysis and simulation results, we demonstrate that the separation performance of the proposed algorithm is similar to that of the per-survivor processing (PSP) algorithm, while its computational complexity is sharply reduced.

Key words: single-channel, separation, Gibbs sampling, QRD-M