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conference paper
Continuous-time distributed estimation with asymmetric mixing
2012
IEEE Statistical Signal Processing Workshop (SSP)
Discrete-time mobile adaptive networks have been successfully used to model self-organization in biological networks. We recently introduced a continuous-time adaptive diffusion strategy with the goal of better modeling physical phenomena governed by continuous-time dynamics. In the present paper we extend our previous work, proposing a new continuous-time diffusion estimation strategy that allows asymmetric mixing matrices. We prove that the new algorithm is stable and has better convergence properties than stand-alone learning for the case of doubly-stochastic mixing matrices.
Type
conference paper
Authors
Publication date
2012
Publisher
Published in
IEEE Statistical Signal Processing Workshop (SSP)
Start page
528
End page
531
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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