| 摘要: |
| 基于非线性盲源分离的维纳系统算法中，采用固定步长导致算法的收敛速度和稳态误差之间存在矛盾，直接影响分离算法的性能。为了解决该问题，提出了基于非线性函数的变步长维纳系统盲源分离方法。该方法将更新的步长以非线性函数的形式引入到分离算法中，使得稳态时参数更新的步长尽可能小，以避免发生振荡。变步长算法在分离过程中的每次更新都会使步长自动进行合理的调整，使得收敛速度提高了53%，误差减小了45%。实验仿真表明，相对原算法，提出的维纳系统盲源分离方法可以更好地分离出信源信号，而且具有较小的误差和较快的收敛速度。 |
| 关键词: 维纳系统 盲源分离 非线性盲源分离 变步长算法 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目(61271115）；吉林省青年科技研究项目(201101110) |
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| An improved variable step size Wiener system blind source separation method |
| ZHAO Liquan,QI Houying |
| () |
| Abstract: |
| In the nonlinear blind source separation algorithm of Wiener system,the fixed step size leads to the contradiction between convergence speed and steady-state error of the algorithm,which directly affects the performance of the separation algorithm.To solve the problem,an algorithm based on variable step size blind source separation method of Wiener system is proposed in this paper.This method that updates the step length in the form of a nonlinear function is introduced into the separation algorithm,makes the steady-state parameters to update the step size as small as possible,so as to avoid oscillating.On the contrary,step increases,speeds up the convergence,increases steady-state error.The variable step size algorithm in the process of separating each update makes step automatically and reasonably adjust,improves the performance of Wiener system blind source separation algorithm.Simulation shows the blind source separation method of Wiener system in this paper can separate source signals better with lower errors and faster convergence speed in comparison with the original algorithm. |
| Key words: Wiener system blind source separation nonlinear blind source separation variable step size algorithm |
《电讯技术》编辑部 