PROJECT TITLE :

Efficient variable step-size diffusion normalised least-mean-square algorithm

ABSTRACT:

An efficient variable step-size diffusion normalised least-mean-square algorithm is proposed via a mean-square deviation (MSD) analysis for the distributed estimation. The proposed algorithm has two distinguishing features for computational efficiency. In the adaptation step, an intermittent adaptation rule that dynamically adjusts an update interval is proposed to reduce the redundant updates. In the diffusion step, instead of the existing combination rules, a selection rule is proposed to select the intermediate estimate of the most reliable node among its neighbour nodes for the estimate at each node. Moreover, to achieve both fast convergence rate and low steady-state error, a variable step size is obtained by minimising the MSD.


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