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Frequency and phase estimation in time series with quasi periodic components

机译:具有准周期分量的时间序列中的频率和相位估计

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摘要

In this article, we consider frequency and phase estimation in a noisy oscillation with potentially non-constant phase increments resulting from an underlying non-constant frequency. A maximum periodogram method on segments is used to estimate the time-varying frequency and a subsequent least squares approach to estimate the phase. A key problem addressed in this article is the question how to set up a meaningful concept of asymptotic statistics for this model. This problem is solved by a special infill asymptotics concept. We use this concept to prove consistency and asymptotic normality of the estimates. Furthermore, the phase estimate is compared to the Hilbert transform in a simulation.
机译:在本文中,我们考虑在噪声振荡中的频率和相位估计,其中潜在的非恒定相位增量是由潜在的非恒定频率引起的。段上的最大周期图方法用于估计时变频率,随后的最小二乘法用于估计相位。本文解决的一个关键问题是如何为该模型建立有意义的渐近统计概念。通过特殊的填充渐近概念可以解决此问题。我们使用这个概念来证明估计的一致性和渐近正态性。此外,在仿真中将相位估计与希尔伯特变换进行比较。

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