access icon free Efficient variable step-size diffusion normalised least-mean-square algorithm

© The Institution of Engineering and Technology
Received 18/11/2014, Published 23/02/2015

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.

Inspec keywords: least mean squares methods; filtering theory

Other keywords: adaptive filtering algorithms; steady-state error; mean-square deviation analysis; variable step-size diffusion normalised least-mean-square algorithm; distributed estimation; MSD; diffusion step; fast convergence rate

Subjects: Filtering methods in signal processing; Signal processing theory; Interpolation and function approximation (numerical analysis); Interpolation and function approximation (numerical analysis)

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      • 1. Blondel, V.D., Hendrickx, J.M., Olshevsky, A., Tsitsiklis, J.N.: ‘Convergence in multi agent coordination, consensus, and flocking’. Proc. Joint 44th IEEE Conf. Decision Control Eur. Control Conf. (CDC-ECC), Seville, Spain, December 2005, pp. 2996–3000.
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2014.4061
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