DocumentCode
1968295
Title
Signal processing with factor graphs: Beamforming and Hilbert transform
Author
Loeliger, Hans-Andrea ; Reller, C.
Author_Institution
Dept. of Inf. Technol. & Electr. Eng., ETH Zurich, Zurich, Switzerland
fYear
2013
fDate
10-15 Feb. 2013
Firstpage
1
Lastpage
4
Abstract
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.
Keywords
Hilbert transforms; Kalman filters; array signal processing; graph theory; message passing; smoothing methods; time-domain analysis; Gaussian message passing; Hilbert transform; Kalman filtering; Kalman smoothing; arbitrary temporal resolution; beamforming; continuous-time linear state space models; digital continuous-time signal estimation; discrete-time observations; factor graphs; signal processing; time-domain sensor array processing; Array signal processing; Computational modeling; Estimation; Kalman filters; Transforms; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory and Applications Workshop (ITA), 2013
Conference_Location
San Diego, CA
Print_ISBN
978-1-4673-4648-1
Type
conf
DOI
10.1109/ITA.2013.6502952
Filename
6502952
Link To Document