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    易叶青, 林亚平, 林 牧, 李小龙, 王 雷. 基于遗传算法的盲源信号分离[J]. 计算机研究与发展, 2006, 43(2): 244-252.
    引用本文: 易叶青, 林亚平, 林 牧, 李小龙, 王 雷. 基于遗传算法的盲源信号分离[J]. 计算机研究与发展, 2006, 43(2): 244-252.
    Yi Yeqing, Lin Yaping, Lin Mu, Li Xiaolong, Wang Lei. Blind Source Separation Based on Genetic Algorithm[J]. Journal of Computer Research and Development, 2006, 43(2): 244-252.
    Citation: Yi Yeqing, Lin Yaping, Lin Mu, Li Xiaolong, Wang Lei. Blind Source Separation Based on Genetic Algorithm[J]. Journal of Computer Research and Development, 2006, 43(2): 244-252.

    基于遗传算法的盲源信号分离

    Blind Source Separation Based on Genetic Algorithm

    • 摘要: 从混合观测数据向量中恢复不可观测的各个源信号是阵列处理和数据分析的一个典型问题.独立分量分析是解决该问题的新技术,而基于四阶累计量的联合对角化(JADE)算法是独立分量分析最常用的算法,但此算法在k>2时得到近似解,且结果不精确.提出了一种基于遗传算法盲源信号分离的算法,此算法克服了JADE算法的不足,理论分析和仿真结果表明了该算法的可行性和有效性.

       

      Abstract: Recovering the unobserved source signals from their mixtures is a typical problem in array processing and data analysis. Independent component analysis (ICA) is a new and powerful method to solve this problem. JADE (joint approximate decomposition of eigen matrices) based on 4th-order cumulants is a common approach for ICA. However, it can only get approximate solution when k>2 and the results are not accurate. In this paper, a blind source separation based on genetic algorithm is proposed. The analysis and simulations suggest that the scheme is feasible and effective.

       

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