AutoSpec: detection of narrowband frequency changes in time series

Pub Date : 2023-01-01 DOI:10.4310/21-sii703
D. Stoffer
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Abstract

Most established techniques that search for structural breaks in time series have a difficult time identifying small changes in the process, especially when looking for narrowband frequency changes. The problem is that many of the techniques assume very smooth local spectra and tend to produce overly smooth estimates. The problem of over-smoothing tends to produce spectral estimates that miss slight frequency changes because frequencies that are close together will be lumped into one frequency. The goal of this work is to develop techniques that concentrate on detecting slight frequency changes by requiring a high degree of resolution in the frequency domain.
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AutoSpec:检测窄带频率变化的时间序列
大多数在时间序列中寻找结构断裂的现有技术很难识别过程中的微小变化,特别是在寻找窄带频率变化时。问题是,许多技术假设非常光滑的局部光谱,往往产生过于光滑的估计。过度平滑的问题往往会产生漏掉轻微频率变化的频谱估计,因为接近的频率会被集中到一个频率上。这项工作的目标是开发一种技术,通过在频域要求高分辨率来集中检测轻微的频率变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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