JOURNAL ARTICLE

Steady-State Analysis of Diffusion LMS Adaptive Networks With Noisy Links

Azam KhaliliMohammad Ali TinatiAmir RastegarniaJonathon A. Chambers

Year: 2011 Journal:   IEEE Transactions on Signal Processing Vol: 60 (2)Pages: 974-979   Publisher: Institute of Electrical and Electronics Engineers

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:
Mean squared error Steady state (chemistry) Mathematics Monotonic function Square (algebra) Least mean squares filter Diffusion Adaptive filter Applied mathematics Computer science Statistics Algorithm Mathematical analysis

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Citation History

Topics

Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Sparse and Compressive Sensing Techniques
Physical Sciences →  Engineering →  Computational Mechanics
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