TL;DR
Cinderella is a software tool that quantitatively compares time series in the frequency domain by calculating probabilities of coincident peaks, aiding in distinguishing true signals from artifacts.
Contribution
It introduces a novel method for frequency domain comparison of time series, with two modes for assessing signal coincidence and artifact presence.
Findings
Effective in identifying coincident signals across datasets.
Supports multiple dataset analysis simultaneously.
Provides probabilistic assessment of signal authenticity.
Abstract
{\sc Cinderella} is a software solution for the quantitative comparison of time series in the frequency domain. It assigns probabilities to coincident peaks in the DFT amplidude spectra of the datasets under consideration. Two different modes are available. In conditional mode, {\sc Cinderella} examines target and comparison datasets on the assumption that the latter contain artifacts only, returning the conditional probability of a target signal, although there is a coincident signal in the comparison data within the frequency resolution. In composed mode, the probability of coincident signal components in both target and comparison data is evaluated. {\sc Cinderella} permits to examine multiple target and comparison datasets at once.
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Taxonomy
TopicsTime Series Analysis and Forecasting