Generative modeling of temporal signal features using hierarchical probabilistic graphical models

Abstract

We propose generative modeling algorithms that analyze the temporal features of non-stationary signals and represent their temporal structural dependencies using hierarchical probabilistic graphical models. First, several template sampling methods are introduced to embed the temporal signal features into multiple instantiations of statistical variables… (More)

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@article{Gang2011GenerativeMO, title={Generative modeling of temporal signal features using hierarchical probabilistic graphical models}, author={Ren Gang and Gregory Bocko and Justin Lundberg and Dave Headlam and Mark F. Bocko}, journal={2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE)}, year={2011}, pages={307-312} }