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首页> 外文期刊>International Journal of Information and Communication Technology >A novel method for blind signal separation of single-channel and time-frequency overlapped multi-component signal
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A novel method for blind signal separation of single-channel and time-frequency overlapped multi-component signal

机译：一种单通道时频交叠多分量信号盲信号分离的新方法

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摘要

In this paper, a novel blind signal separation (BSS) method of single-input multi-output (SIMO) system is proposed based on the periodicity of independent components, which can separate time-frequency overlapped multi-component signal effectively. It adopts the technique of changing single-channel recordings vector into virtual multi-channel measurement matrix. Singular value decomposition (SVD) method is utilised to decompose the matrix. Singular value ratio (SVR) spectrum can be calculated by changing the virtual multi-channel measurement matrix. Combining SVR spectrum and the periodic characteristic of independent components, the independent components are isolated successfully. The source number can be estimated by the peak value of SVR spectrum. The simulation results demonstrate the effectiveness of the proposed algorithm in this paper and show the method can guarantee high separation accuracy in low signal-noise-ratio (SNR) environment.
机译：提出了一种基于独立分量周期性的单输入多输出（SIMO）系统盲信号分离（BSS）方法，该方法可以有效地分离时频重叠的多分量信号。它采用将单通道记录矢量更改为虚拟多通道测量矩阵的技术。利用奇异值分解（SVD）方法分解矩阵。可以通过更改虚拟多通道测量矩阵来计算奇异值比（SVR）频谱。结合SVR频谱和独立分量的周期性特征，成功地隔离了独立分量。可以通过SVR频谱的峰值来估计源编号。仿真结果证明了该算法的有效性，证明了该方法在低信噪比环境下可以保证较高的分离精度。

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