Bayesian spectrum estimation of unevenly sampled nonstationary data

Abstract

Spectral estimation methods typically assume stationarity and uniform spacing between samples of data. The non-stationarity of real data is usually accommodated by windowing methods, while the lack of uniformly-spaced samples is typically addressed by methods that “fill in” the data in some way. This paper presents a new approach to both of… (More)
DOI: 10.1109/ICASSP.2002.5744891

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