Bayesian interpolation in a dynamic sinusoidal model with application to packet-loss concealment

Jesper Kjær Nielsen, Mads Græsbøll Christensen, Ali Taylan Cemgil, Simon J. Godsill, Søren Holdt Jensen

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

2 Citationer (Scopus)
134 Downloads (Pure)

Abstrakt

In this paper, we consider Bayesian interpolation and parameter estimation in a dynamic sinusoidal model. This model is more flexible than the static sinusoidal model since it enables the amplitudes and phases of the sinusoids to be time-varying. For the dynamic sinusoidal model, we derive a Bayesian inference scheme for the missing observations, hidden states and model parameters of the dynamic model. The inference scheme is based on a Markov chain Monte Carlo method known as Gibbs sampler. We illustrate the performance of the inference scheme to the application of packet-loss concealment of lost audio and speech packet
OriginalsprogEngelsk
TidsskriftProceedings of the European Signal Processing Conference
Vol/bind2010
Sider (fra-til)239-243
ISSN2076-1465
StatusUdgivet - 24 aug. 2010
BegivenhedEUSIPCO 2010 - Aalborg, Danmark
Varighed: 23 aug. 2010 → …

Konference

KonferenceEUSIPCO 2010
LandDanmark
ByAalborg
Periode23/08/2010 → …

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