2022/07/25 by Eduardo Martini, Martini, Eduardo
Chemistry · Computer Science · Mathematics · #Advanced Statistical Methods and Models #Blind Source Separation Techniques #Data Analysis #FOS: Physical sciences #Spectroscopy and Chemometric Analyses #Statistics and Probability (physics.data-an)
paper · pdf · doi:10.48550/arxiv.2207.12159
openalex publication_date 2022/07/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Periodogram methods are widely used for the estimation of power- and cross-spectra, of which Welch's method is the most popular. Previous studies have analyzed the variance of the power spectra estimates and developed analytical probability functions, showing that the approach is unbiased when applied to white-noise signals or in the limit of infinite window lengths. However, no explicit expression for the estimation bias is available for more complex signals when finite windows are used. In this study, we show that, for finite window lengths, Welch's method is biased for all signals other than the white-noise signal. A novel two-window approach that is unbiased when applied to signals with bounded correlation lengths is proposed. Numerical experiments are used to illustrate the advantages of the novel approach.