Convolutive blind separation algorithm based on complex Givens matrix and bat optimization

Zhi-cheng JIA; Da-wei HAN; Lei CHEN; Yan-ju GUO; Hao-da XU

doi:10.11959/j.issn.1000-436x.2016138

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Convolutive blind separation algorithm based on complex Givens matrix and bat optimization

Academic paper | 更新时间：2024-06-05

- Convolutive blind separation algorithm based on complex Givens matrix and bat optimization
- Journal of Communications Vol. 37, Issue 7, Pages: 107-117(2016)
- 作者机构：
  
  1. 河北工业大学电子信息工程学院，天津 300401
  2. 天津大学精密仪器与光电子工程学院，天津 300072
  3. 天津商业大学信息工程学院，天津 300134
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61401307);The China Postdoctoral Science Foundation(2014M561184);Tianjin Research Program of Application Foundation and Advanced Technology(15JCYBJC17100)
- DOI：10.11959/j.issn.1000-436x.2016138
  CLC： TN911.7
- Online First：2016-07，
  
  Published：25 July 2016
- 稿件说明：
移动端阅览
Zhi-cheng JIA, Da-wei HAN, Lei CHEN, et al. Convolutive blind separation algorithm based on complex Givens matrix and bat optimization[J]. Journal of Communications, 2016, 37(7): 107-117.
DOI：

Zhi-cheng JIA, Da-wei HAN, Lei CHEN, et al. Convolutive blind separation algorithm based on complex Givens matrix and bat optimization[J]. Journal of Communications, 2016, 37(7): 107-117. DOI： 10.11959/j.issn.1000-436x.2016138.

摘要

针对传统卷积混合盲分离待求参数多、分离效果易受分离矩阵初值影响的局限性，提出了基于复Givens矩阵与蝙蝠优化的频域求解算法。算法采用复Givens矩阵表示分离矩阵，减少了待求参数，降低了求解难度和计算量。利用蝙蝠算法代替梯度算法优化求解旋转角度完成各频点线性瞬时混合复信号的盲分离，全局收敛性更强。此外，由于对源信号的先验知识要求较少，可以分离服从多种分布的信号。仿真实验表明，该算法可有效地实现卷积混合盲分离。

Abstract

For the limitations such as many unknown parameters

the separation accuracy was easily influenced by initial value of separation matrix in traditional convolutive blind separation

a kind of frequency method based on complex Givens matrix and bat optimization was proposed. The algorithm used a series of complex Givens matrices to denote separation matrix

it reduced unknown parameters

decreased the difficulty and the amount of calculations as a result. Be-sides

the algorithm utilized bat algorithm instead of conventional gradient algorithm to optimize rotation angles and completed the separation of complex linear instantaneous mixing signals at each frequency point

the use of bat algorithm made the optimization ability better. In addition

little prior information was needed and signals following various distri-butions could be separated. Simulation results show that the proposed method can realize convolutive blind separation ef-ficiently.

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references

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