| 基于粒子群算法的盲源信号分离 |
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| 引用本文： | 吴新杰,崔春阳.基于粒子群算法的盲源信号分离[J].辽宁大学学报(自然科学版),2009,36(2):125-128. |
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| 作者姓名： | 吴新杰 崔春阳 |
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| 作者单位： | 辽宁大学,物理学院,辽宁,沈阳,110036 |
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| 基金项目： | 辽宁省教育厅科研项目，华北电力大学电站设备状态监测与控制教育部重点实验室开放基金 |
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| 摘 要： | 当源信号个数大于2,联合对角化（JADE）算法在盲源信号分离时效果不理想.提出了一种基于粒子群算法（PSO）的盲源信号分离（BSS）算法.该算法利用PSO算法代替JADE算法中的联合对角化操作,以混合信号的峭度为目标函数,采用独立分量分析的方法,对瞬时混合的信号进行了盲分离,理论分析和仿真结果表明了该算法的可行性和有效性.
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| 关 键 词： | 盲源信号分离 粒子群算法 联合对角化 |
Blind Source Separation Based on Particle Swarm Optimization |
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| WU Xin-jie,CUI Chun-yang.Blind Source Separation Based on Particle Swarm Optimization[J].Journal of Liaoning University(Natural Sciences Edition),2009,36(2):125-128. |
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| Authors: | WU Xin-jie CUI Chun-yang |
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| Institution: | College of Physics;Liaoning University;Shenyang 110036;China |
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| Abstract: | When the number of signal is more than 2,the results of BSS(blind source separation) by JADE(joint approximate decomposition of eigen matrices) are not desirable.In this paper,a new algorithm of BSS based on PSO(particle swarm optimization) is proposed.The operation of joint diagonalization is instead of PSO.Using kurtosis of the mixed signal to the target function of BSS,it succeeds to separate the instantaneous mixed signal by the method of independent component analysis.The analysis and simulations sugge... |
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| Keywords: | blind source separation particle swarm optimization joint diagonalization |
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