DocumentCode
3352597
Title
Estimating a Function from Noisy Sensor Data: A Factor Graph Approach
Author
Barros, João ; Tuechler, Michael
Author_Institution
Univ. of Porto, Porto
fYear
2007
fDate
14-16 March 2007
Firstpage
777
Lastpage
781
Abstract
The combination of graphical models and belief propagation algorithms has found wide acceptance in the design of communication systems. We extend the general framework of joint source-channel decoding on graphs to account for estimation problems in which the goal is not to decode the entire data set but to estimate a function of the transmitted data. This problem is deemed relevant e.g. in the context of wireless sensor networks.
Keywords
combined source-channel coding; decoding; graph theory; wireless sensor networks; belief propagation algorithms; communication systems; factor graph approach; function estimation; graphical models; joint source-channel decoding; noisy sensor data; wireless sensor networks; Algorithm design and analysis; Belief propagation; Covariance matrix; Graphical models; Grid computing; Iterative decoding; Redundancy; Sensor systems; Space technology; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Sciences and Systems, 2007. CISS '07. 41st Annual Conference on
Conference_Location
Baltimore, MD
Print_ISBN
1-4244-1063-3
Electronic_ISBN
1-4244-1037-1
Type
conf
DOI
10.1109/CISS.2007.4298413
Filename
4298413
Link To Document