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Blind source separation with variable step-size method based on a reference separation system

机译:基于参考分离系统的可变步长盲源分离

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Variable step-size methods are effective methods to solve the problem of choosing step size in adaptive blind source separation process. This paper proposes a novel variable step-size method based on a reference separation system for blind source separation. In view of the correlation between the estimated source signals and original source signals increases along with iteration, the method introduces a reference separation system to approximately estimate the correlation which is utilized to update the step-size. The performance in terms of cross-talking error of the proposed algorithm is analyzed. Simulation results show that the proposed method exhibits superior convergence and better steady-state performance compared with the fixed step-size method in the noise free case, and converges faster than classical variable step-size methods in both stationary and non-stationary environments.
机译:可变步长法是解决自适应盲源分离过程中选择步长问题的有效方法。本文提出了一种基于参考分离系统的可变步长大小的盲源分离新方法。考虑到估计的源信号和原始源信号之间的相关性随着迭代的增加而增加,该方法引入了参考分离系统以近似地估计相关性,该相关性被用于更新步长。分析了该算法在串扰误差方面的性能。仿真结果表明,在无噪声情况下,与固定步长法相比,该方法具有更好的收敛性和更好的稳态性能,并且在固定和非平稳环境下,其收敛速度都快于经典的可变步长法。

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