conference paper
Steady-state performance of incremental learning over distributed networks for non-Gaussian data
2008
9th International Conference on Signal Processing
In this paper, the steady-state performance of the distributed least mean-squares (dLMS) algorithm within an incremental network is evaluated without the restriction of Gaussian distributed inputs. Computer simulations are presented to verify the derived performance expressions.
Type
conference paper
Author(s)
Date Issued
2008
Publisher
Published in
9th International Conference on Signal Processing
Start page
227
End page
230
Editorial or Peer reviewed
REVIEWED
Written at
OTHER
EPFL units
| Event name | Event place | Event date |
Beijing, China | October 26-29, 2008 | |
Available on Infoscience
December 19, 2017
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