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Target Signal Extraction Method Based on Enhanced ICA with Reference

机译:基于增强ICA的目标信号提取方法参考

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摘要

Target signal extraction has a great potential for applications. To solve the problem of error extraction of target signals in the current constrained independent component analysis (cICA) method, an enhanced independent component analysis with reference (EICA-R) method is proposed. The new algorithm establishes a unified cost function, which combines the negative entropy contrast function and the distance metric function. The EICA-R method transforms the constrained optimization problem into unconstrained optimization problem to overcome the problem of threshold setting of distance metric function in constrained optimization problem. The theoretical analysis and simulation experiment show that the proposed EICA-R algorithm overcomes the problem of the error extraction of the existing algorithm and improves the reliability of the target signal extraction.
机译:目标信号提取具有巨大的应用潜力。为了解决当前约束的独立分量分析(CICA)方法中目标信号的误差提取问题,提出了参考(EICA-R)方法的增强的独立分量分析。新算法建立了一个统一的成本函数,它结合了负熵对比功能和距离度量功能。 EICA-R方法将约束优化问题转换为无约束优化问题,以克服约束优化问题中距离度量函数的阈值设置问题。理论分析和仿真实验表明,所提出的EICA-R算法克服了现有算法的误差提取问题,提高了目标信号提取的可靠性。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第18期|4128438.1-4128438.12|共12页
  • 作者单位

    IEU Sci Ave Zhengzhou 450001 Henan Peoples R China|LEETC POB 061 Luoyang 471000 Peoples R China;

    IEU Sci Ave Zhengzhou 450001 Henan Peoples R China;

    IEU Sci Ave Zhengzhou 450001 Henan Peoples R China;

    IEU Sci Ave Zhengzhou 450001 Henan Peoples R China;

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