@inproceedings{86669e488f1f4e41a1fbc98bb88ea67e,
title = "Convergence of a distributed parameter estimator for sensor networks with local averaging of the estimates",
abstract = "The paper addresses the convergence of a decentralized Robbins-Monro algorithm for networks of agents. This algorithm combines local stochastic approximation steps for finding the root of an objective function, and a gossip step for consensus seeking between agents. We provide verifiable sufficient conditions on the stochastic approximation procedure and on the network so that the decentralized Robbins-Monro algorithm converges to a consensus. We also prove that the limit points of the algorithm correspond to the roots of the objective function. We apply our results to Maximum Likelihood estimation in sensor networks.",
author = "P. Bianchi and G. Fort and W. Hachem and J. Jakubowicz",
year = "2011",
month = aug,
day = "18",
doi = "10.1109/ICASSP.2011.5947170",
language = "English",
isbn = "9781457705397",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "3764--3767",
booktitle = "2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings",
note = "36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 ; Conference date: 22-05-2011 Through 27-05-2011",
}