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Online bayesian inference in some time-frequency representations of non-stationary processes
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Everitt, Richard G., Andrieu, Christophe and Davy, Manuel (2013) Online bayesian inference in some time-frequency representations of non-stationary processes. IEEE Transactions on Signal Processing, 61 (22). pp. 5755-5766. doi:10.1109/TSP.2013.2280128 ISSN 1053-587X.
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Official URL: https://doi.org/10.1109/TSP.2013.2280128
Abstract
The use of Bayesian inference in the inference of time-frequency representations has, thus far, been limited to offline analysis of signals, using a smoothing spline based model of the time-frequency plane. In this paper we introduce a new framework that allows the routine use of Bayesian inference for online estimation of the time-varying spectral density of a locally stationary Gaussian process. The core of our approach is the use of a likelihood inspired by a local Whittle approximation. This choice, along with the use of a recursive algorithm for non-parametric estimation of the local spectral density, permits the use of a particle filter for estimating the time-varying spectral density online. We provide demonstrations of the algorithm through tracking chirps and the analysis of musical data.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Journal or Publication Title: | IEEE Transactions on Signal Processing | ||||
Publisher: | IEEE | ||||
ISSN: | 1053-587X | ||||
Official Date: | 29 August 2013 | ||||
Dates: |
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Volume: | 61 | ||||
Number: | 22 | ||||
Page Range: | pp. 5755-5766 | ||||
DOI: | 10.1109/TSP.2013.2280128 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
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