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Adaptive Variant of the Surrogate Data Technology for Enhancing the Effectiveness of Signal Spectral Analysis Using Eigenstructure Methods

机译:替代数据技术的自适应变型,使用本征结构方法增强信号频谱分析的有效性

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摘要

The problem of enhancing the effectiveness of spectral analysis of signals observed against the background of noise by the Root-MUSIC method has been considered using the surrogate data technology implemented by adapting the algorithm of phase randomization of the Fourier transform samples of the initial data in relation to the signal-to-noise ratio (SNR). The proposed variant of the surrogate data technology was shown to be effective at low values of SNR and a small number of samples. At large values of SNR an additive variant of the surrogate data technology actually does not cause an emergence of surrogate interference typical for nonadaptive variant. The proposed variant of the technology can be applied in combination with other methods of spectral analysis.
机译:已经考虑使用替代数据技术来提高通过Root-MUSIC方法在噪声背景下观察到的信号的频谱分析的有效性的问题,该替代数据技术是通过将初始数据的傅里叶变换样本的相位随机算法与信噪比(SNR)。替代数据技术的拟议变体在低SNR和少量样本的情况下被证明是有效的。在较大的SNR值下,替代数据技术的加性变量实际上不会引起非自适应变量典型的替代干扰的出现。该技术的建议变体可以与其他光谱分析方法结合使用。

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