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conference paper
Unsupervised algorithms for distributed estimation over adaptive networks
2012
Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers (ASILOMAR)
This work shows how to develop distributed versions of block blind estimation techniques that have been proposed before for batch processing. Using diffusion adaptation techniques, data are accumulated at the nodes to form estimates of the auto-correlation matrices and to carry out local SVD and/or Cholesky decomposition steps. Local estimates at neighborhoods are then aggregated to provide online streaming estimates of the parameters of interest. Simulation results illustrate the performance of the algorithms.
Type
conference paper
Authors
Publication date
2012
Publisher
Published in
Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers (ASILOMAR)
Start page
1780
End page
1783
Peer reviewed
REVIEWED
EPFL units
Event name | Event place | Event date |
Pacific Grove, CA, USA | November 4-7, 2012 | |
Available on Infoscience
December 19, 2017
Use this identifier to reference this record