Signal processing with factor graphs: Beamforming and Hilbert transform
Hans‐Andrea Loeliger, Christoph Reller · 2013
Continuous-time linear state space models with discrete-time observations enable digital estimation of continuous-time signals with arbitrary temporal resolution by means of Kalman filtering/smoothing or Gaussian message passing in the corresponding factor graph. In this paper, we demonstrate the application of this approach to time-domain sensor array processing and to an emulation of the Hilbert transform.