@inproceedings{cdcb4303f71c4f63ad426fa5967166d1,
title = "Distributed collaborative parameter estimation based on bias compensation",
abstract = "This paper presents the study of the problem of distributed parameter estimation by bias compensated recursive least squares (BCRLS) algorithm over adaptive networks. The nodes in the distributed network have a common objective to estimate parameter vector in a collaborative strategy. Traditional recursive least squares (RLS) estimator is biased in case that both the regressor and the output response are corrupted by stationary additive noise. A real-time estimation algorithm of noise variance is proposed, which nodes get the estimation of objective parameter bias. Based on collaborative strategy, we propose a diffusion bias compensated recursive least-squares algorithm. Simulation results show that the BCRLS algorithm has better estimation accuracy than traditional RLS algorithm, and compared with the local estimators, the diffusion BCRLS algorithm has lower mean square error (MSE).",
keywords = "bias compensation, collaborative estimation, diffusion, least-squares, noise estimation",
author = "Shuo Wang and Jia, {Li Juan} and Dou, {Chao Ping}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014 ; Conference date: 08-10-2014 Through 10-10-2014",
year = "2014",
month = nov,
day = "17",
doi = "10.1109/SOLI.2014.6960707",
language = "English",
series = "Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "135--138",
booktitle = "Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014",
address = "United States",
}