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@TECHREPORT{barber:rr05-87,
         author = {Barber, David},
       projects = {Idiap},
          title = {Efficient Kalman Smoothing for Harmonic State-Space Models},
           type = {Idiap-RR},
         number = {Idiap-RR-87-2005},
           year = {2005},
    institution = {IDIAP},
       abstract = {Harmonic probabilistic models are common in signal analysis. Framed as a linear-Gaussian state-space model, smoothed inference scales as $O(TH^2)$ where $H$ is twice the number of frequencies in the model and $T$ is the length of the time-series. Due to their central role in acoustic modelling, fast effective inference in this model is of some considerable interest. We present a form of `rotation-corrected' low-rank approximation for the backward pass of the Rauch-Tung-Striebel smoother. This provides an effective approximation with computation complexity $O(TSH)$ where $S$ is the rank of the approximation.},
            pdf = {https://publications.idiap.ch/attachments/reports/2005/barber-idiap-rr-05-87.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2005/barber-idiap-rr-05-87.ps.gz},
ipdmembership={learning},
}