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Some practical remarks on the extended Prony's method of spectrum analysis

机译:关于扩展Prony频谱分析方法的一些实用评论

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摘要

Prony's method of spectrum analysis models a time series as a linear combination of complex exponentials plus a white noise. The performance of the method is very dependent on the peculiarity of the signal to be analyzed. Four algorithms for autoregressive estimation are experimentally compared to provide valid indications for the choice of the most suitable one for estimating the Prony's parameters. L. Marple's algorithm (1980) seems to be the best, while well-known facts about bias in frequency estimation produced by Burg's algorithm are confirmed; nevertheless, it performs better than the covariance and the singular-value-decomposition-based algorithms.
机译:Prony的频谱分析方法将时间序列建模为复杂指数和白噪声的线性组合。该方法的性能非常取决于要分析的信号的特性。实验比较了四种用于自回归估计的算法,以为选择Prony参数最合适的算法提供有效的指示。 L. Marple算法(1980)似乎是最好的,而Burg算法产生的有关频率估计偏差的众所周知的事实也得到了证实。但是,它的性能要优于协方差和基于奇异值分解的算法。

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