Improved statistical sparse decomposition principle method for underdetermined blind source signal recovery

doi:10.19682/j.cnki.1005-8885.2019.1030

中国邮电高校学报(英文版) ›› 2019, Vol. 26 ›› Issue (6): 94-102.doi: 10.19682/j.cnki.1005-8885.2019.1030

• Signal processing • 上一篇

Improved statistical sparse decomposition principle method for underdetermined blind source signal recovery

Wang Chuanchuan, Zeng Yonghu, Wang Liandong, Fu Weihong

1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang 471003, China
2. State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, China

收稿日期:2019-09-02 修回日期:2019-12-22 出版日期:2019-12-31 发布日期:2020-03-10
通讯作者: Wang Chuanchuan, E-mail: wangchuan1083@126.com E-mail:wangchuan1083@126.com
作者简介:Wang Chuanchuan, E-mail: wangchuan1083@126.com

Improved statistical sparse decomposition principle method for underdetermined blind source signal recovery

Wang Chuanchuan, Zeng Yonghu, Wang Liandong, Fu Weihong

1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang 471003, China
2. State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, China

Received:2019-09-02 Revised:2019-12-22 Online:2019-12-31 Published:2020-03-10
Contact: Wang Chuanchuan, E-mail: wangchuan1083@126.com E-mail:wangchuan1083@126.com
About author:Wang Chuanchuan, E-mail: wangchuan1083@126.com

摘要/Abstract

摘要： Aiming at the statistical sparse decomposition principle (SSDP) method for underdetermined blind source signal recovery with problem of requiring the number of active signals equal to that of the observed signals, which leading to the application bound of SSDP is very finite, an improved SSDP (ISSDP) method is proposed. Based on the principle of recovering the source signals by minimizing the correlation coefficients within a fixed time interval, the selection method of mixing matrix's column vectors used for signal recovery is modified, which enables the choose of mixing matrix's column vectors according to the number of active source signals self-adaptively. By simulation experiments, the proposed method is validated. The proposed method is applicable to the case where the number of active signals is equal to or less than that of observed signals, which is a new way for underdetermined blind source signal recovery.

关键词:

underdetermined blind source separation, signal recovery, ISSDP

Abstract: Aiming at the statistical sparse decomposition principle (SSDP) method for underdetermined blind source signal recovery with problem of requiring the number of active signals equal to that of the observed signals, which leading to the application bound of SSDP is very finite, an improved SSDP (ISSDP) method is proposed. Based on the principle of recovering the source signals by minimizing the correlation coefficients within a fixed time interval, the selection method of mixing matrix's column vectors used for signal recovery is modified, which enables the choose of mixing matrix's column vectors according to the number of active source signals self-adaptively. By simulation experiments, the proposed method is validated. The proposed method is applicable to the case where the number of active signals is equal to or less than that of observed signals, which is a new way for underdetermined blind source signal recovery.

Key words:

underdetermined blind source separation, signal recovery, ISSDP

中图分类号:

TN911

Wang Chuanchuan, Zeng Yonghu, Wang Liandong, Fu Weihong.

Improved statistical sparse decomposition principle method for underdetermined blind source signal recovery

[J]. The Journal of China Universities of Posts and Telecommunications, 2019, 26(6): 94-102.

参考文献

References
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Improved statistical sparse decomposition principle method for underdetermined blind source signal recovery

Improved statistical sparse decomposition principle method for underdetermined blind source signal recovery

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