DocumentCode :
1360014
Title :
Steady-State Analysis of Diffusion LMS Adaptive Networks With Noisy Links
Author :
Khalili, Azam ; Tinati, Mohammad Ali ; Rastegarnia, Amir ; Chambers, Jonathon A.
Author_Institution :
Fac. of Electr. & Comput. Eng., Univ. of Tabriz, Tabriz, Iran
Volume :
60
Issue :
2
fYear :
2012
Firstpage :
974
Lastpage :
979
Abstract :
In this correspondence, we analyze the effects of noisy links on the steady-state performance of diffusion least-mean-square (LMS) adaptive networks. Using the established weighted spatial-temporal energy conservation argument, we derive a variance relation which contains moments that represent the effects of noisy links. We evaluate these moments and derive closed-form expressions for the mean-square deviation (MSD), excess mean-square error (EMSE) and mean-square error (MSE) to explain the steady-state performance at each individual node. The derived expressions, supported by simulations, reveal that unlike the ideal link case, the steady-state MSD, EMSE, and MSE curves are not monotonically increasing functions of the step-size parameter when links are noisy. Moreover, the diffusion LMS adaptive network does not diverge due to noisy links.
Keywords :
adaptive signal processing; energy conservation; least mean squares methods; EMSE curve; LMS adaptive network; closed-form expression; diffusion least mean square adaptive network; mean square deviation; mean square error; noisy link; steady-state MSD; steady-state performance analysis; step-size parameter; weighted spatial-temporal energy conservation argument; Adaptive systems; Data models; Least squares approximation; Noise measurement; Peer to peer computing; Signal processing algorithms; Steady-state; Adaptive networks; distributed estimation; energy conservation; noisy links;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2011.2173338
Filename :
6059517
Link To Document :
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