计算机科学 ›› 2013, Vol. 40 ›› Issue (Z11): 15-17.

• 无线网络与通信 • 上一篇    下一篇

时变混合系统的自适应动量项快速盲源分离算法

陈海平,张杭,路威,杨柳,周轩   

  1. 解放军理工大学通信工程学院 南京210007;解放军理工大学通信工程学院 南京210007;解放军理工大学通信工程学院 南京210007;解放军理工大学通信工程学院 南京210007;解放军理工大学通信工程学院 南京210007
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金:欠定情况下基于扰信分离的信干比增强方法研究(61001106),国家“973”基金项目:无线网络主动认知方法研究(2009CB320400)资助

Adaptive Momentum Fast Blind Source Separation Algorithm for Time-varying Mixing System

CHEN Hai-ping,ZHANG Hang,LU Wei,YANG Liu and ZHOU Xuan   

  • Online:2018-11-16 Published:2018-11-16

摘要: 现有的多数盲源分离算法都是假设混合系统是时不变的,然而在实际的通信系统中混合系统常常是时变的。提出一种渐变的时变混合系统模型,并针对该渐变模型和现有的突变模型提出了收敛速度较快的盲源分离算法,该算法使用均方误差指数加权和的形式定义代价函数,并且在算法学习过程中引入了自适应动量项。仿真结果表明,所提算法在时变环境中较现有算法有更快的收敛速度,能有效地跟踪时变混合系统,并能抗多音干扰。

关键词: 盲源分离,自适应动量项,时变,收敛速度

Abstract: Most of existing blind source separation algorithms are developed by assuming that the mixing matrix is fixed.However,the mixing matrix is commonly time-varying in practical communication system.In this paper,a model of gradually time-varying mixing system is proposed.Aiming at the model and the existing model of abruptly time-va-rying mixing system,a fast blind source separation algorithm is proposed by using the exponentially weighted sum of error squares as the cost function and adding the adaptive momentum term to the learning rule.Simulation results show that the proposed algorithm converges faster than existing algorithm and trace the time-varying system effectively.

Key words: Blind source separation,Adaptive momentum term,Time-varying,Convergence rate

[1] Caridso J F,Laheld B H.Equivariant adaptive source separation [J].IEEE Transactions of Signal Processing,1996,44(12):3017-3030
[2] Hyvarinen A.Fast and robust fixed-point algorithms for independent component analysis [J].IEEE Transactions on Neural Networks,1999,10(3):626-634
[3] Vicente Z,Pierre C.Robust independent component analysis by iterative maximization of the kurtosis contrast with algebraic optimal step size [J].IEEE Transactions on Neural Networks,2010,21(2):248-261
[4] Yuan Lian-xi,Wang Wen-wu, Chambers J A.Variable step-size sign natural gradient algorithm for sequential blind source separation [J].IEEE Signal Processing Letters,2005,12(8):589-592
[5] 付卫红,史凡,刘乃安.适用于时变信道环境的盲源分离算法[J].电子科技大学学报,2012,41(4):512-515
[6] 蒋照菁,辜方林,张杭.一种基于NPCA的变步长盲源分离算法[J].计算机工程与应用,2013,49(8):206-208
[7] 欧世峰,高颖,赵晓晖.自适应组合型盲源分离算法及其优化方案[J].电子与信息学报,2011,33(5):1243-1247
[8] 刘建强.非平稳环境中的盲源分离算法研究[D].西安:西安电子科技大学,2009
[9] Enescu M,Koivunen V.Tracking time-varying mixing system in blind separation[C]∥Sensor Array and Multichannel Signal Processing Workshop.2000:291-295
[10] 辜方林,张杭,李伦辉.基于非线性主成分分析的自适应变步长盲源分离算法[J].计算机应用,2013,33(5):1233-1236
[11] Puskal P,Umut O,Deniz E,et al.Recursive complex BSS via generalized eigendecomposition and application in image rejection for BPSK[J].Signal Processing,2007,88(2008):1368-1381
[12] Amari S,Chen T P,Cichocki A.Stability analysis of learning algorithms for blind source separation[J].Neural Network,1997,10(8):1345-1351

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!