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conference paper
Diffusion LMS for source and process estimation in sensor networks
2012
IEEE Statistical Signal Processing Workshop (SSP)
We develop a least mean-squares (LMS) diffusion strategy for sensor network applications where it is desired to estimate parameters of physical phenomena that vary over space. In particular, we consider a regression model with space-varying parameters that captures the system dynamics over time and space. We use a set of basis functions such as sinusoids or B-spline functions to replace the space-variant (local) parameters with space-invariant (global) parameters, and then apply diffusion adaptation to estimate the global representation. We illustrate the performance of the algorithm via simulations.
Type
conference paper
Authors
Publication date
2012
Publisher
Published in
IEEE Statistical Signal Processing Workshop (SSP)
Start page
165
End page
168
Peer reviewed
REVIEWED
EPFL units
Event name | Event place | Event date |
Ann Arbor, MI, USA | August 5-8, 2012 | |
Available on Infoscience
December 19, 2017
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