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A Spatial Diffusion Strategy for Tap-Length Estimation Over Adaptive Networks

Lookup NU author(s): Professor Jonathon Chambers



We consider the distributed estimation problem, where a set of nodes is required to collectively estimate some parameter vector of interest with unknown or variable tap-length. In practice, a sufficiently large filter length is utilized in such contexts to avoid a large excess mean square error at steady state, thereby resulting in slower convergence rate and increased computations. In this work we motivate and propose a new diffusion-based variable tap-length algorithm, which is able to track tap-length changes during the convergence process. Theoretical analyses are provided in terms of steady-state performance and convergence performance, which are verified by simulation results. Some general criteria for parameter selections are also given according to the performance analyses. Numerical simulations demonstrate the efficiency of the proposed algorithm as compared with existing techniques, and robustness to parameter settings provided the parameter choice guidelines are satisfied.

Publication metadata

Author(s): Zhang YG, Wang CC, Zhao L, Chambers JA

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Signal Processing

Year: 2015

Volume: 63

Issue: 17

Pages: 4487-4501

Print publication date: 01/09/2015

Online publication date: 02/06/2015

Acceptance date: 15/05/2015

Date deposited: 08/02/2017

ISSN (print): 1053-587X

ISSN (electronic): 1941-0476

Publisher: IEEE


DOI: 10.1109/TSP.2015.2440182


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Funder referenceFunder name
China Scholarship Council
2014T70309China Postdoctoral Science Foundation
61371173National Natural Science Foundation of China
2013M530147China Postdoctoral Science Foundation
61001154National Natural Science Foundation of China
61201409National Natural Science Foundation of China
LBH-TZ0505Heilongjiang Postdoctoral Fund
HEUCFX41307Fundamental Research Funds for the Central Universities of Harbin Engineering University
LBH-Z13052Heilongjiang Postdoctoral Fund